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PubMed2001

The impact of genotyping error on family-based analysis of quantitative traits.

Errors in genotyping can substantially influence the power to detect linkage using affected sib-pairs, but it is not clear what effect such errors have on quantitative trait analyses. Here we use Monte Carlo simulation to examine the influence of genotyping error on multipoint vs two-point analysis, variable map density, locus effect size and allele frequency in quantitative trait linkage and association studies of sib-pairs. The analyses are conducted using variance components methods. We contrast the effects of error on quantitative trait analyses with those on the affected sib-pair design. The results indicate that genotyping error influences linkage studies of affected sib pairs more severely than studies of quantitative traits in unselected sibs. In situations of modest effect size, 5% genotyping error eliminates all supporting evidence for linkage to a true susceptibility locus in affected pairs, but may only result in a loss of 15% of linkage information in random pairs. Multipoint analysis does not suffer substantially more than two-point analysis; for moderate error rates (< 5%), multipoint analysis with error is more powerful than two-point with no error. Map density does not appear to be an important factor for linkage analysis. QTL association analyses of common alleles are reasonably robust to genotyping error but power can be affected dramatically with rare alleles.

Alleles↗
PubMed2002

On the mapping of quantitative trait loci at marker and non-marker locations.

Previous studies have noted that the estimated positions of a large proportion of mapped quantitative trait loci (QTLs) coincide with marker locations and have suggested that this indicates a bias in the mapping methodology. In this study we predict the expected proportion of QTLs with positions estimated to be at the location of a marker and further examine the problem using simulated data. The results show that the higher proportion of putative QTLs estimated to be at marker positions compared with non-marker positions is an expected consequence of the estimation methods. The study initially focused on a single interval with no QTLs and was extended to include multiple intervals and QTLs of large effect. Further, the study demonstrated that the larger proportion of estimated QTL positions at the location of markers was not unique to linear regression mapping. Maximum likelihood produced similar results, although the accumulation of positional estimates at outermost markers was reduced when regions outside the linkage group were also considered. The bias towards marker positions is greatest under the null hypothesis of no QTLs or when QTL effects are small. This study discusses the impact the findings could have on the calculation of thresholds and confidence intervals produced by bootstrap methods.

Animals↗
PubMed2001

Genetic mapping of quantitative trait loci governing longevity of Caenorhabditis elegans in recombinant-inbred progeny of a Bergerac-BO x RC301 interstrain cross.

Recombinant-inbred populations, generated from a cross between Caenorhabditis elegans strains Bergerac-BO and RC301, were used to identify quantitative trait loci (QTL) affecting nematode longevity. Genotypes of young controls and longevity-selected worms (the last-surviving 1% from a synchronously aged population) were assessed at dimorphic transposon-specific markers by multiplex polymerase chain reaction. The power of genetic mapping was enhanced, in a novel experimental design, through map expansion by accrual of recombinations over several generations, internally controlled longevity selection from a genetically heterogeneous, homozygous population, and selective genotyping of extremely long-lived worms. Analysis of individual markers indicated seven life-span QTL, situated near markers on chromosomes I (tcbn2), III (stP127), IV (stP13), V (stP6, stP23, and stP128), and X (stP41). These loci were corroborated, and mapped with increased precision, by nonparametric interval mapping-which supported all loci implicated by single-marker analysis. In addition, a life-span QTL on chromosome II (stP100-stP196), was significant only by interval mapping. Congenic lines were constructed for the longevity QTL on chromosomes III and X, by backcrossing the Bergerac-BO QTL allele into an RC301 background with selection for flanking markers. Survival data for these lines demonstrated consistent and significant effects of each QTL on life span.

Alleles↗
PubMed2006

Genetic linkage between growth rate and the intersterility genes S and P in the basidiomycete Heterobasidion annosum s.lat.

Quantitative trait loci (QTL) for mycelial growth rate were identified and positioned on a genetic linkage map of Heterobasidion annosum sensu lato (s.l.), an important root rot pathogen on conifers. The mycelial growth rate among 84 progeny isolates were analysed in two different temperature regimes, 12 and 24 degrees C on malt extract agar and found to segregate as a continuous character. The assay identified three QTL for growth rate at low temperature positioned on the linkage groups 1, 17 and 19 with peak LOD values of 3.2, 2.9 and 4.8, respectively. At the QTL for high temperature growth, peak LOD values of 1.3, 2.8 and 2.2, were identified. The three QTL for the low temperature regime explained 20.9, 18.1 and 24.0 % of the variation in the mycelial growth rate, respectively. The broad-sense heritability was estimated to be 0.97 and 0.95 for growth rate at low and high temperatures, respectively. Two of the QTL for the mycelial growth rate were shown to be tightly linked to the intersterility genes S and P, which control mating within and between closely related species and intersterility groups of H. annosum s.lat. Isolates with a plus allele at the intersterility loci had a higher growth rate than isolates that harboured minus alleles.

Basidiomycota↗
PubMed2006

QTL analysis of popping fold and the consistency of QTLs under two environments in popcorn.

Popping fold (PF) is the most important quality trait in popcorn. In this study, a total of 259 F2:3 families, derived from the cross between a dent corn inbred Dan232 and a popcorn inbred N04, were evaluated for their popping folds in replicated experiments under two environments. Of 613 simple sequence repeat (SSR) primer pairs screened, 183 pairs were selected to construct a genetic linkage map with the genetic distance of 1,762.2 cM (centimorgan) and on average 9.63 cM every marker. Quantative trait loci (QTL) were identified, and their genetic effects were estimated using CIM (composite interval mapping) method. The interactions among QTLs detected were calculated using MIM (multiple interval mapping) method. In all, 22 QTLs were detected, and only 5 of them were common under two environments. Contribution to phenotypic variation of a single QTL varied from 3.07% to 12.84%, and total contributions of all QTLs under two environments were 66.46% and 51.90%, respectively. Three QTLs (qPF-6-1, qPF-8-1 and qPF-1-3) with more than 10% contributions were observed. The additive effects were larger than dominant effects for most QTLs. The amount of QTLs showing additive, partially dominant, dominant and over-dominant effects were 4, 5, 0, 2 in spring sowing and 2, 5, 2, 2 in summer sowing, respectively. There were only 2.60% pairs of QTLs or maker intervals expressing AA, DA or DD interactions.

Environment↗
PubMed2003

Substitution mapping of a blood pressure quantitative trait locus to a 2.73 Mb region on rat chromosome 1.

OBJECTIVE: To improve the localization of a blood pressure quantitative trait locus (BP QTL) on rat chromosome (RNO) 1. METHODS: Congenic substrains were derived from the progenitor congenic strains S.LEW(D1Mco4X1) and S.LEW(D1Mco4X5) which previously localized a BP QTL (region 2) to a 17cM interval on RNO1. The newly developed congenic substrains, along with control Dahl salt-sensitive (S) rats were fed a 2% NaCl diet for 24 days before their BP was compared by both tail-cuff and radiotelemetry methods. RESULTS: By comparing BP of these congenic substrains to that of S rats, we have refined the location of the BP QTL2 region to a 2.73 Mb genomic interval that contains 19 annotated genes in the latest rat genome assembly (version 2.1). Slc9a3, the gene encoding the Na(+)/H(+) exchanger 3, originally a candidate gene in the BP QTL2 region, is excluded based on its map location. CONCLUSION: Substitution mapping was used to reduce a BP QTL on RNO1 from 17 centimorgans (cM) to approximately 1.4 cM (= 2.73 Mb). This region now contains 19 annotated rat candidate genes.

Animals↗
PubMed2003

Congenic strains of mice for verification and genetic decomposition of quantitative trait loci for femoral bone mineral density.

Peak femoral volumetric bone mineral density (femoral bone mineral density) in C57BL/6J (B6) 4-month-old female mice is 50% lower than in C3H/HeJ (C3H) and 34% lower than in CAST/EiJ (CAST) females. Genome-wide analyses of (B6 x C3H)F2 and (B6 x CAST)F2 4-month-old female progeny demonstrated that peak femoral bone mineral density is a complex quantitative trait associated with genetic loci (QTL) on numerous chromosomes (Chrs) and with trait heritabilities of 83% (C3H) and 57% (CAST). To test the effect of each QTL on femoral bone mineral density, two sets of loci (six each from C3H and CAST) were selected to make congenic strains by repeated backcrossing of donor mice carrying a given QTL-containing chromosomal region to recipient mice of the B6 progenitor strain. At the N6F1 generation, each B6.C3H and B6.CAST congenic strain (statistically 98% B6-like in genomic composition) was intercrossed to obtain N6F2 progeny for testing the effect of each QTL on femoral bone mineral density. In addition, the femoral bone mineral density QTL region on Chr 1 of C3H was selected for congenic subline development to facilitate fine mapping of this strong femoral bone mineral density locus. In 11 of 12 congenic strains, 6 B6.C3H and 5 B6.CAST, femoral bone mineral density in mice carrying c3h or cast alleles in the QTL regions was significantly different from that of littermates carrying b6 alleles. Differences also were observed in body weight, femoral length, and mid-diaphyseal periosteal circumference among these 11 congenic strains when compared with control littermates; however, these latter three phenotypes were not consistently correlated with femoral bone mineral density. Analyses of eight sublines derived from the B6.C3H-1T congenic region revealed two QTLs: one located between 36.9 and 49.7 centiMorgans (cM) and the other located between 73.2 and 100.0 cM distal to the centromere. In conclusion, these congenic strains provide proof of principle that many QTLs identified in the F2 analyses for femoral bone mineral density exert independent effects when transferred and expressed in a common genetic background. Furthermore, significant differences in femoral bone mineral density among the congenic strains were not consistently accompanied by changes in body weight, femur length, or periosteal circumference. Finally, decomposition of QTL regions by congenic sublines can reveal additional loci for phenotypes assigned to a QTL region and can markedly refine genomic locations of quantitative trait loci, providing the opportunity for candidate gene testing.

Alleles↗
PubMed2000

A mixed-model approach to mapping quantitative trait loci in barley on the basis of multiple environment data.

In this article, I propose a mixed-model method to detect QTL with significant mean effect across environments and to characterize the stability of effects across multiple environments. I demonstrate the method using the barley dataset by the North American Barley Genome Mapping Project. The analysis raises the need for mixed modeling in two different ways. First, it is reasonable to regard environments as a random sample from a population of target environments. Thus, environmental main effects and QTL-by-environment interaction effects are regarded as random. Second, I expect a genetic correlation among pairs of environments caused by undetected QTL. I show how random QTL-by-environment effects as well as genetic correlations are straightforwardly handled in a mixed-model framework. The main advantage of this method is the ability to assess the stability of QTL effects. Moreover, the method allows valid statistical inferences regarding average QTL effects.

Crosses, Genetic↗
PubMed2002

Parental genetic contributions in the AXB and BXA recombinant inbred mouse strains.

Recombinant inbred (RI) strains are a valuable tool in mouse genetics to rapidly map the location of a new locus. Because RI strains have been typed for hundreds of genetic markers, the genotypes of individual strains within an RI set can be examined to identify specific strain(s) containing the desired region(s) of interest (e.g., one or more quantitative trait loci, QTLs) for subsequent phenotype testing. Specific RI strains might also be identified for use as progenitors in the construction of consomic (chromosome substitution strains or CSSs) or congenic lines or for use in the RI strain test (RIST). To quickly identify the genetic contributions of the parental A/J (A) and C57BL/6J (B) strains, we have generated chromosome maps for each commercially available AXB and BXA RI strain, in which the genetic loci are color-coded to signify the parent of origin. To further assist in strain selection for further breeding schemes, the percentages of A and B parental contributions were calculated, based on the total number of typed markers in the database for each strain. With these data, one can rapidly select the RI strain(s) carrying the desired donor and recipient strain region(s). Because points of recombination are known, starting with RI mice to generate CSSs or congenic lines immediately reduces genomewide screening to those donor-strain regions not already homozygous in the recipient strain. Two examples are presented to demonstrate potential uses of the generated chromosome maps: to select RI strains to construct congenic lines and to perform an RIST for Aliq1, a QTL linked to ozone-induced acute lung injury survival.

Animals↗
PubMed2002

Application of non-parametric bootstrap methods to estimate confidence intervals for QTL location in a beef cattle QTL experimental population.

Empirical confidence intervals (CIs) for the estimated quantitative trait locus (QTL) location from selective and non-selective non-parametric bootstrap resampling methods were compared for a genome scan involving an Angus x Brahman reciprocal fullsib backcross population. Genetic maps, based on 357 microsatellite markers, were constructed for 29 chromosomes using CRI-MAP V2.4. Twelve growth, carcass composition and beef quality traits (n = 527-602) were analysed to detect QTLs utilizing (composite) interval mapping approaches. CIs were investigated for 28 likelihood ratio test statistic (LRT) profiles for the one QTL per chromosome model. The CIs from the non-selective bootstrap method were largest (87 7 cM average or 79-2% coverage of test chromosomes). The Selective II procedure produced the smallest CI size (42.3 cM average). However, CI sizes from the Selective II procedure were more variable than those produced by the two LOD drop method. CI ranges from the Selective II procedure were also asymmetrical (relative to the most likely QTL position) due to the bias caused by the tendency for the estimated QTL position to be at a marker position in the bootstrap samples and due to monotonicity and asymmetry of the LRT curve in the original sample.

Animals↗
PubMed2004

Mapping of quantitative trait loci (QTLs) affecting autumn freezing resistance and phenology in Salix.

Quantitative trait locus (QTL) analysis was performed at different time points during cold-acclimation of a tetraploid F(2 ) Salix pedigree. The pedigree ( n=92) was derived from a cross between a frost-susceptible diploid female clone 'Jorunn' ( Salix viminalis) and a frost resistant hexaploid male clone 'SW901290' ( Salix dasyclados). Freezing resistance, height growth increment and number of new leaves were assessed at days 0, 12, 20, 24, 31 and 42 of a short day-low temperature (SD-LT) hardening regime, while the initiation of shoot tip abscission and shoot tip abscission were measured daily. Height increment, dry-to-fresh weight ratio and number of new leaves were also measured in a replicated field trial. Freezing resistance was determined from electrolyte leakage of leaf tissues and from visual injuries on stem segments, after exposure to a predetermined freeze-thaw stress. Using a genetic map of the F(2) composed of 432 single-dose AFLP markers, a total of 19 genomic regions controlling freezing resistance (10) and phenological traits (9) before and during cold-acclimation (SD-LT) were identified. The magnitude of the phenotypic variation explained by each freezing resistance locus varied over acclimation time (0-45%), and there was no time point at which all the QTLs could be detected. The single QTL detected for non-acclimated freezing resistance did not reach significance at any time point during cold-acclimation, suggesting an independent genetic relationship between non-acclimated and acclimated resistance to freezing in Salix. Five of the loci associated with freezing resistance shared common intervals with loci controlling phenological traits. Of the 14 QTLs controlling autumn freezing resistance and/or phenological traits in the indoors experiment, six (43%) were associated with autumn phenology-related traits, i.e. height increment, dry-to-fresh weight ratio and number of new leaves, measured in the field. A major locus with multi-trait association in both indoor and outdoor experiments was detected.

Acclimatization↗
PubMed2001

The replicability of QTLs for murine alcohol preference drinking behavior across eight independent studies.

On the basis of eight independent quantitative trait loci (QTL) studies of ethanol (alcohol) preference drinking in mice, a meta-analysis was carried out to examine the replicability of QTLs across studies and to enhance the power of QTL detection and parameter estimation. To avoid genetic heterogeneity, we analyzed only studies of mapping populations derived from the C57BL/6 (B6) and DBA/2 (D2) inbred progenitor strains. Because these studies were carried out in five different laboratories, there were substantial differences in testing procedure, data analysis, and especially in the choice of mapping population (BXD recombinant inbred strains, F2, backcross, selected lines, or congenic strains). Despite this, we found several QTLs that were sufficiently robust as to appear consistently across studies given the strengths and weaknesses of the mapping populations employed. These were on Chromosomes (Chrs) 2 (proximal to mid), 3 (mid to distal), 4 (distal), and 9 (proximal to mid). The P value for each of these QTLs, combined across all applicable studies, ranged from 10(-7) to 10(-15), with the additive effect of each QTL accounting for 3-5% of the trait variance extrapolated to an F2 population. Two other QTLs on Chrs 1 (distal) and 11 (mid) were less consistent, but still reached overall significance (P <.0001).

Alcohol Drinking↗
PubMed2004

Bayesian point estimation of quantitative trait loci.

In this article, we consider the problem of the estimation of quantitative trait loci (QTL), those chromosomal regions at which genetic information affecting some quantitative trait is encoded. Generally the number of such encoding sites is unknown, and associations between neutral molecular marker genotypes and observed trait phenotypes are sought to locate them. We consider a Bayesian model for simple experimental designs, and discuss the existing approaches to inference for this problem. In particular, we focus on locating positions of the best candidate markers segregating for the trait, a situation which is of primary interest in comparative mapping. We introduce a loss function for estimating both the number of QTL and their location, and we illustrate its application via simulated and real data.

Animals↗
PubMed2006

Characterization of the DGAT1 mutations and the CSN1S1 promoter in the German Angeln dairy cattle population.

The identification of quantitative trait loci (QTL) and genes with influence on milk production traits has been the objective of various mapping studies in the last decade. In the centromeric region of Bos taurus autosome (BTA) 14, the acyl-CoA:diacylglycerol acyltransferase1 gene (DGAT1) has been identified as the most likely causative gene underlying a QTL for milk fat yield and content. Recently, a second polymorphism in the promoter of DGAT1 emerged as an additional source of variation. In this study, the frequencies and the effects of alleles at the DGAT1 K232A and at the DGAT1 promoter variable number of tandem repeat (VNTR) locus on BTA14, and of alleles at the CSN1S1 (alpha(S1)-casein-encoding gene) promoter on BTA6 in the German Angeln dairy cattle population were investigated. Analyzed traits were milk, fat, protein, lactose, and milk energy yield, fat, protein, lactose, and milk energy content and somatic cell score. The lysine variant of the DGAT1 K232A mutation showed significant effects for most of the milk production traits. A specific allele of the DGAT1 promoter VNTR showed significant effects on the traits lactose yield and content, milk energy content, and SCS compared with the other alleles. Additionally, a regulation mechanism between the DGAT1 K232A mutation and the DGAT1 promoter VNTR was found for fat yield and content, which could be caused by an upper physiological bound for the effects of the DGAT1 gene. At the CSN1S1 promoter, 2 of 4 alleles showed significant allele substitution effects on the milk yield traits.

Alleles↗
PubMed2003

Modifier genes and heart failure.

Recent progress in genomic applications have led to a better understanding of the relationship between genetic background and cardiovascular diseases such as heart failure. A considerable component of the variability in heart failure outcome is due to modifier genes, i.e. genes that are not involve in the genesis of a disease but modify the severity of the phenotypic expression once the disease has developed. The strategy most commonly used to identify modifier genes is based on association studies between the severity of the phenotype of the disease (morbidity and/or mortality) and the sequence variation(s) of selected candidate gene(s). This strategy has showed that several polymorphisms of the beta1 and beta2 adrenergic receptors genes and the angiotensin converting enzyme gene are correlated to the prognosis of patients with heart failure. Recently, we have applied an experimental strategy, known as genome mapping, for the identification of heart failure modifier genes. Genome mapping has previously been used with success to identify the genes involved in the development of both monogenic and multifactorial diseases. We have showed that the prognosis of heart failure mice, induced through overexpressing calsequestrin, is linked to 2 Quantitative Trait Loci (QTL) localized on chromosome 2 and 3. Using both strategies (candidate gene and genome mapping) should allow us to identify a number of modifier genes that may provide a more rational approach to identify patients at risk for disease and response to therapy.

Calsequestrin↗
PubMed2005

Resistance gene analogues in sugarcane and sorghum and their association with quantitative trait loci for rust resistance.

Fifty-four different sugarcane resistance gene analogue (RGA) sequences were isolated, characterized, and used to identify molecular markers linked to major disease-resistance loci in sugarcane. Ten RGAs were identified from a sugarcane stem expressed sequence tag (EST) library; the remaining 44 were isolated from sugarcane stem, leaf, and root tissue using primers designed to conserved RGA motifs. The map location of 31 of the RGAs was determined in sugarcane and compared with the location of quantitative trait loci (QTL) for brown rust resistance. After 2 years of phenotyping, 3 RGAs were shown to generate markers that were significantly associated with resistance to this disease. To assist in the understanding of the complex genetic structure of sugarcane, 17 of the 31 RGAs were also mapped in sorghum. Comparative mapping between sugarcane and sorghum revealed syntenic localization of several RGA clusters. The 3 brown rust associated RGAs were shown to map to the same linkage group (LG) in sorghum with 2 mapping to one region and the third to a region previously shown to contain a major rust-resistance QTL in sorghum. These results illustrate the value of using RGAs for the identification of markers linked to disease resistance loci and the value of simultaneous mapping in sugarcane and sorghum.

Chromosome Mapping↗
PubMed2001

A mammary gland EST showing linkage disequilibrium to a milk production QTL on bovine Chromosome 14.

As part of a genome scan, ESTs derived from mammary gland tissue of a lactating cow were used as candidate genes for quantitative trait loci (QTL), affecting milk production traits. Resource families were genotyped with 247 microsatellite markers and 4 polymorphic ESTs. It was shown by linkage analysis that one of these ESTs, KIEL_E8, mapped to the centromeric region of bovine Chromosome (Chr) 14. Regression analysis revealed the presence of a QTL, with significant effect on milk production, in this chromosome region, and analysis of variance showed no significant interaction of marker genotype and family. The estimated significant differences between homozygous marker genotypes were 140 kg milk, -5.02 kg fat yield, and 2.58 kg protein yield for the first 100 days of lactation. Thus, there was strong evidence for a complete or nearly complete linkage disequilibrium between KIEL_E8 and the QTL. To identify the biological function of KIEL_E8, we extended the sequence for 869 bp by 5'-RACE. A 560-bp fragment of this shows a 90.9% similarity to a gene encoding a cysteine- and histidine-rich cytoplasmic protein in mouse. Although such a protein may have a regulatory function for lactation and a linkage disequilibrium between the EST marker and the QTL has been observed, it remains to be elucidated whether they are identical or not. Nevertheless, KIEL_E8 will be an efficient marker to perform marker-assisted selection in the Holstein-Friesian population.

Alleles↗
PubMed2002

Precise mapping of breakpoints in conserved synteny between human chromosome 1 and pig chromosomes 4, 6 and 9.

Previous comparative mapping suggested that at least five pig chromosomes (Sscr4, 6, 9, 10 and 14) share homology with human chromosome 1 (Hsap1). A significant quantitative trait loci (QTL) for fat deposition has been identified on Sscr4 that appears to be near the junction region between Sscr4 and Sscr9 relative to Hsap1. It is of interest to define the boundaries of conserved synteny between pig chromosomes and Hsap1 to use human map information to identify putative comparative positional candidates for this QTL. Eleven genes, including Janus kinase 1 (JAK1), Prostaglandin E receptor3 (PTGER3), urate oxidase (UOX), coagulation factor 3 (F3), vascular cell adhesion molecule 1 (VCAM1), ribosomal protein L5 (RPL5), POU domain, class 2, transcription factor 1 (POU2F1), coagulation factor 5 (F5), Prostaglandin endoperoxide synthase-2 (PTGS2), myosin binding protein H (MYBPH) and Antithrombin III (SERPINC1), were selected to refine the boundaries of the blocks of conserved synteny between Hsap1 and pig chromosomes. Pig sequence tagged sites (STSs) were developed and used to physically map these 11 genes using a somatic cell hybrid panel. Eight loci have been mapped by using fluorescent in situ hybridization (FISH) to improve map resolution. Heterologous FISH was used to refine the location of VCAM1 on human chromosomes. In addition, human yeast artificial chromosomes (YACs) were mapped by heterologous FISH on pig metaphases to refine the boundaries of the regions of homology between Sscr4 and Sscr9 on Hsap1. Results from this study suggest the precise break in conserved synteny on Hsap1 corresponding to the Sscr4/6 and Sscr4/9 transitions are most likely on the Hsap1p22 and Hsap1q24-25 regions, respectively. Further, our data predict that Hsap1q21-24 is a candidate region for the backfat QTL localized to Sscr4.

Animals↗