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PubMed2000

Fine mapping of quantitative trait loci using linkage disequilibria with closely linked marker loci.

A multimarker linkage disequilibrium mapping method was developed for the fine mapping of quantitative trait loci (QTL) using a dense marker map. The method compares the expected covariances between haplotype effects given a postulated QTL position to the covariances that are found in the data. The expected covariances between the haplotype effects are proportional to the probability that the QTL position is identical by descent (IBD) given the marker haplotype information, which is calculated using the genedropping method. Simulation results showed that a QTL was correctly positioned within a region of 3, 1.5, or 0.75 cM in 70, 62, and 68%, respectively, of the replicates using markers spaced at intervals of 1, 0.5, and 0.25 cM, respectively. These results were rather insensitive to the number of generations since the QTL occurred and to the effective population size, except that 10 generations yielded rather poor estimates of the QTL position. The position estimates of this multimarker disequilibrium mapping method were more accurate than those from a single marker transmission disequilibrium test. A general approach for identifying QTL is suggested, where several stages of disequilibrium mapping are used with increasingly dense marker spacing.

Chromosome Mapping↗
PubMed2001

Bayesian methods for quantitative trait loci mapping based on model selection: approximate analysis using the Bayesian information criterion.

We describe an approximate method for the analysis of quantitative trait loci (QTL) based on model selection from multiple regression models with trait values regressed on marker genotypes, using a modification of the easily calculated Bayesian information criterion to estimate the posterior probability of models with various subsets of markers as variables. The BIC-delta criterion, with the parameter delta increasing the penalty for additional variables in a model, is further modified to incorporate prior information, and missing values are handled by multiple imputation. Marginal probabilities for model sizes are calculated, and the posterior probability of nonzero model size is interpreted as the posterior probability of existence of a QTL linked to one or more markers. The method is demonstrated on analysis of associations between wood density and markers on two linkage groups in Pinus radiata. Selection bias, which is the bias that results from using the same data to both select the variables in a model and estimate the coefficients, is shown to be a problem for commonly used non-Bayesian methods for QTL mapping, which do not average over alternative possible models that are consistent with the data.

Alleles↗
PubMed2001

Consequences of recombination rate variation on quantitative trait locus mapping studies. Simulations based on the Drosophila melanogaster genome.

We examine the effect of variation in gene density per centimorgan on quantitative trait locus (QTL) mapping studies using data from the Drosophila melanogaster genome project and documented regional rates of recombination. There is tremendous variation in gene density per centimorgan across this genome, and we observe that this variation can cause systematic biases in QTL mapping studies. Specifically, in our simulated mapping experiments of 50 equal-effect QTL distributed randomly across the physical genome, very strong QTL are consistently detected near the centromeres of the two major autosomes, and few or no QTL are often detected on the X chromosome. This pattern persisted with varying heritability, marker density, QTL effect sizes, and transgressive segregation. Our results are consistent with empirical data collected from QTL mapping studies of this species and its close relatives, and they explain the "small X-effect" that has been documented in genetic studies of sexual isolation in the D. melanogaster group. Because of the biases resulting from recombination rate variation, results of QTL mapping studies should be taken as hypotheses to be tested by additional genetic methods, particularly in species for which detailed genetic and physical genome maps are not available.

Animals↗
PubMed2003

Recent advances in human quantitative-trait-locus mapping: comparison of methods for discordant sibling pairs.

Extreme discordant sibling pairs (EDSPs) are theoretically powerful for the mapping of quantitative-trait loci (QTLs) in humans. EDSPs have not been used much in practice, however, because of the need to screen very large populations to find enough pairs that are extreme and discordant. Given appropriate statistical methods, another alternative is to use moderately discordant sibling pairs (MDSPs)--pairs that are discordant but not at the far extremes of the distribution. Such pairs can be powerful yet far easier to collect than extreme discordant pairs. Recent work on statistical methods for QTL mapping in humans has included a number of methods that, though not developed specifically for discordant pairs, may well be powerful for MDSPs and possibly even EDSPs. In the present article, we survey the new statistics and discuss their applicability to discordant pairs. We then use simulation to study the type I error and the power of various statistics for EDSPs and for MDSPs. We conclude that the best statistic(s) for discordant pairs (moderate or extreme) is (are) to be found among the new statistics. We suggest that the new statistics are appropriate for many other designs as well-and that, in fact, they open the way for the exploration of entirely novel designs.

Genetics, Population↗
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

Genome scan for quantitative trait loci linked to high-density lipoprotein cholesterol: The NHLBI Family Heart Study.

We conducted a genome-wide linkage scan for quantitative trait loci influencing total HDL-cholesterol (HDL-C) concentration in a sample of 1027 whites from 101 families participating in the NHLBI Family Heart Study. To maximize the relative contribution of genetic components of variance to the total variance of HDL-C, the HDL-C phenotype was adjusted for age, age(2), body mass index, and Family Heart Study field center, and standardized HDL-C residuals were created separately for men and women. All analyses were completed by the variance components method, as implemented in the program GENEHUNTER using 383 anonymous markers typed at the NHLBI Mammalian Genotyping Service in Marshfield, Wis. Evidence for linkage of residual HDL-C was detected near marker D5S1470 at location 39.9 cM from the p-terminal of chromosome 5 (LOD=3.64). Suggestive linkage was detected near marker D13S1493 at location 27.5 cM on chromosome 13 (LOD=2.36). We conclude that at least 1 genomic region is likely to harbor a gene that influences interindividual variation in HDL cholesterol.

Adolescent↗
PubMed2000

Power of quantitative trait locus mapping for polygenic binary traits using generalized and regression interval mapping in multi-family half-sib designs.

A generalized interval mapping (GIM) method to map quantitative trait loci (QTL) for binary polygenic traits in a multi-family half-sib design is developed based on threshold theory and implemented using a Newton-Raphson algorithm. Statistical power and bias of QTL mapping for binary traits by GIM is compared with linear regression interval mapping (RIM) using simulation. Data on 20 paternal half-sib families were simulated with two genetic markers that bracketed an additive QTL. Data simulated and analysed were: (1) data on the underlying normally distributed liability (NDL) scale, (2) binary data created by truncating NDL data based on three thresholds yielding data sets with three different incidences, and (3) NDL data with polygenic and QTL effects reduced by a proportion equal to the ratio of the heritabilities on the binary versus NDL scale (reduced-NDL). Binary data were simulated with and without systematic environmental (herd) effects in an unbalanced design. GIM and RIM gave similar power to detect the QTL and similar estimates of QTL location, effects and variances. Presence of fixed effects caused differences in bias between RIM and GIM, where GIM showed smaller bias which was affected less by incidence. The original NDL data had higher power and lower bias in QTL parameter estimates than binary and reduced-NDL data. RIM for reduced-NDL and binary data gave similar power and estimates of QTL parameters, indicating that the impact of the binary nature of data on QTL analysis is equivalent to its impact on heritability.

Algorithms↗
PubMed2005

Further mapping of quantitative trait loci for postnatal growth in an inter-sub-specific backcross of wild Mus musculus castaneus and C57BL/6J mice.

We performed a quantitative trait locus (QTL) analysis of eight body weights recorded weekly from 3 weeks to 10 weeks after birth and two weight gains recorded between 3 weeks and 6 weeks, and between 6 weeks and 10 weeks in an inter-sub-specific backcross population of wild Mus musculus castaneus mice captured in the Philippines and the common inbred strain C57BL/6J ( M. musculus domesticus ), to elucidate the complex genetic architecture of body weight and growth. Interval mapping identified 17 significant QTLs with main effects on 11 chromosomes. In particular, the main effect of the most potent QTL on proximal chromosome 2 increased linearly with age, whereas other QTLs exerted effects on either the early or late growth period. Surprisingly, although wild mice displayed 60% of the body size of their C57BL/6J counterparts, the wild-derived allele enhanced growth at two QTLs. Interestingly, five of the 17 main-effect QTLs identified had significant epistatic interaction effects. Five new epistatic QTLs with no main effects were identified on different chromosomes or regions. For one pair of epistatic QTLs, mice that were heterozygous for the wild-derived allele at one QTL and homozygous for that allele at another QTL exhibited the most rapid growth in all four possible genotypic combinations. Out of the identified QTLs, several showed significant sex-specific effects.

Animals↗
PubMed2006

Substitution mapping in dahl rats identifies two distinct blood pressure quantitative trait loci within 1.12- and 1.25-mb intervals on chromosome 3.

Substitution mapping was used to refine the localization of blood pressure (BP) quantitative trait loci (QTL) within the congenic region of S.R-Edn3 rats located at the q terminus of rat chromosome 3 (RNO3). An F2(SxS.R-Edn3) population (n=173) was screened to identify rats having crossovers within the congenic region of RNO3 and six congenic substrains were developed that carry shorter segments of R-rat-derived RNO3. Five of the six congenic substrains had significantly lower BP compared to the parental S rat. The lack of BP lowering effect demonstrated by the S.R(ET3x5) substrain and the BP lowering effect retained by the S.R(ET3x2) substrain together define the RNO3 BP QTL-containing region as approximately 4.64 Mb. Two nonoverlapping substrains, S.R(ET3x1) and S.R(ET3x6), had significantly lower BP compared to the S strain, indicating the presence of two distinct BP QTL in the RNO3 q terminus. The RNO3 q terminus was fine mapped with newly developed polymorphic markers to characterize the extent of the congenic regions. The two RNO3 BP QTL regions were thus defined as within intervals of 0.05-1.12 and 0.72-1.25 Mb, respectively. Also important was our difficulty in fine mapping and marker placement in this portion of the rat genome (and thus candidate gene identification) using the available genomic data, including the rat genome sequence.

Animals↗
PubMed2006

Simultaneous fine mapping of multiple closely linked quantitative trait Loci using combined linkage disequilibrium and linkage with a general pedigree.

Within a small region (e.g., <10 cM), there can be multiple quantitative trait loci (QTL) underlying phenotypes of a trait. Simultaneous fine mapping of closely linked QTL needs an efficient tool to remove confounded shade effects among QTL within such a small region. We propose a variance component method using combined linkage disequilibrium (LD) and linkage information and a reversible jump Markov chain Monte Carlo (MCMC) sampling for model selection. QTL identity-by-descent (IBD) coefficients between individuals are estimated by a hybrid MCMC combining the random walk and the meiosis Gibbs sampler. These coefficients are used in a mixed linear model and an empirical Bayesian procedure combines residual maximum likelihood (REML) to estimate QTL effects and a reversible jump MCMC that samples the number of QTL and the posterior QTL intensities across the tested region. Note that two MCMC processes are used, i.e., an (internal) MCMC for IBD estimation and an (external) MCMC for model selection. In a simulation study, the use of the multiple-QTL model clearly removes the shade effects between three closely linked QTL located at 1.125, 3.875, and 7.875 cM across the region of 10 cM, using 40 markers at 0.25-cM intervals. It is shown that the use of combined LD and linkage information gives much more useful information compared to using linkage information alone for both single- and multiple-QTL analyses. When using a lower marker density (11 markers at 1-cM intervals), the signal of the second QTL can disappear. Extreme values of past effective size (resulting in extreme levels of LD) decrease the mapping accuracy.

Chromosome Mapping↗
PubMed2004

Mapping major quantitative trait loci for postnatal growth in an intersubspecific backcross between C57BL/6J and Philippine wild mice by using principal component analysis.

A number of quantitative trait loci (QTLs) for postnatal growth have previously been reported in mice. As effects of the QTLs are usually small and similar to one another in magnitude, it is generally difficult to know which loci are major contributors to postnatal growth. We applied principal component analysis to a genome-wide search for QTLs affecting postnatal growth in body weight weekly recorded from 3 to 10 weeks of age in an intersubspecific backcross population of C57BL/6J inbred mice (Mus musculus domesticus) and wild mice (M. m. castaneus) captured in the Philippines, in order to discover new QTLs from a gene pool of the wild mice and uncover major loci underlying variation in postnatal growth. Principal component analysis classified phenotypic variation in body weights at different ages into two independent principal components: the first principal component (PC1) extracted information on the entire growth process and the second principal component (PC2) contrasted middle (3-6 weeks of age) with late (6-10 weeks) growth phases. Simple interval mapping and composite interval mapping revealed 10 significant QTLs with main effects on PC1 or PC2 on eight chromosomes. Of these, the six main-effect QTLs interacted epistatically with one another or three new additional QTLs on different chromosomal regions without main effects. Several of the identified QTLs with main effects and/or epistatic interaction effects appeared to be sex specific. These results suggest that the identified 13 QTLs, most of which affected the entire growth process, are very important contributors to complex genetic networks of postnatal growth.

Animals↗
PubMed2004

Identification of quantitative trait Loci for anxiety and locomotion phenotypes in rat recombinant inbred strains.

Anxiety disorders are phenotypically complex and may involve multiple genetic influences on many neurotransmitter systems. Rodent tests used to investigate genetic influences on anxiety-like phenotypes have face and predictive validity as models for anxiety in humans. If multiple genes contribute additively to a trait, the trait will be continuously distributed and be amenable to detection of associations between allelic variation at specific chromosomal loci and the phenotypes being studied via quantitative trait loci (QTL) mapping. The elevated plus-maze test provides quantitative measures of both anxiety-like and locomotion phenotypes. Using this test, we assessed four phenotypes in a set of 22 rat recombinant inbred (RI) strains derived from Brown Norway (BN.Lx /Cub) and Spontaneously Hypertensive rat (SHR/Ola) progenitors. QTL analyses were used to determine whether allelic variation at specific chromosomal loci contribute significantly to RI strain-dependent variance in each phenotype. Significant QTL for an anxiety phenotype were found on chromosomes 2, 5, 6, and 7. For a phenotype reflecting both anxiety and locomotion, QTL were found on chromosomes 2, 7, and 8, while for a locomotion phenotype, significant QTL were found on chromosomes 3 and 18.

Alleles↗
PubMed1999

Identification of quantitative trait loci affecting female reproductive traits in a multigeneration Meishan-White composite swine population.

A multigeneration crossbred Meishan-White composite resource population was used to identify quantitative trait loci (QTL) for age at first estrus (AP) and the components of litter size: ovulation rate (OR; number of ova released in an estrous period) and uterine capacity (UC). The population was established by reciprocally mating Meishan (ME) and White composite (WC) pigs. Resultant F1 females were mated to either ME or WC boars to produce backcross progeny (BC) of either 3/4 WC 1/4 ME or 1/4 WC 3/4 ME. To produce the next generation (F3), 3/4 WC 1/4 ME animals were mated to 1/4 WC 3/4 ME animals yielding half-blood (1/2 WC 1/2 ME) progeny. A final generation (F4) was produced by inter se mating F3 animals. Measurements for AP and OR were recorded on 101 BC, 389 F3, and 110 F4 gilts, and UC data were from 101 BC and 110 F4 first parity litters. A genomic scan was conducted with markers (n = 157) spaced approximately 20 cM apart. All parental, F1, BC, and F4 animals but only 84 F3 animals were genotyped and included in this study. The QTL analysis fitted a QTL at 1-cM intervals throughout the genome, and QTL effects were tested using approximate genome-wide significance levels. For OR, a significant (E[false positive] < .05) QTL was detected on chromosome 8, suggestive (E[false positive] < 1.0) QTL were detected on chromosomes 3 and 10, and two additional regions were detected that may possess a QTL (E[false positive] < 2.0) on chromosomes 9 and 15. Two regions possessed suggestive evidence for QTL affecting AP on chromosomes 1 and 10, and one suggestive region on chromosome 8 was identified for UC. Further analyses of other populations of swine are necessary to determine the extent of allelic variation at the identified QTL.

Animals↗
PubMed1998

Successful isolation of a rat chromosome 1 blood pressure quantitative trait locus in reciprocal congenic strains.

Linkage analyses in experimental crosses of hypertensive and normotensive rats have strongly suggested the presence of a quantitative trait locus (QTL) influencing blood pressure on rat chromosome 1, at or near the Sa gene. To confirm the presence of such a locus and move toward identification of the causative gene, we have developed, through targeted breeding over 10 generations using an Sa gene polymorphism to select breeders at each generation, 2 congenic strains, 1 containing a segment of spontaneously hypertensive rat (SHR) chromosome 1 in a Wistar-Kyoto rat (WKY) genetic background (WKY.SHR-Sa), and the other a segment of WKY chromosome 1 in an SHR background (SHR.WKY-Sa). WKY.SHR-Sa contains at least approximately 26 cM of SHR chromosome 1, between markers mD7mit206 and D1Mit2 (and including the SHR allele of the Sa gene), and SHR.WKY-Sa carries at least approximately 15 cM of WKY chromosome 1, between mD7mit206 and D1Wox34 (and including the WKY allele of the Sa gene). Blood pressure of WKY.SHR-Sa rats measured at 16, 20, and 25 weeks of age was significantly higher than that of WKY, whereas blood pressure of SHR.WKY-Sa rats was significantly lower than that of SHR. At 25 weeks, the mean differences in systolic and diastolic blood pressure between WKY.SHR-Sa and WKY were +11.5 mm Hg (P=0.001) and +11.6 mm Hg mm Hg (P<0.001), respectively. The corresponding differences between SHR.WKy-Sa and SHR were -11.3 mm Hg (P=0.002) and -9.1 mm Hg (P=0.005), respectively. The differences represent about one fifth of the blood pressure difference between SHR and WKY. Renal Sa mRNA levels in the congenic strains reflected their Sa allele with a high level in WKY. SHR-Sa and a low level in SHR.WKY-Sa, consistent with previous data suggesting that the level of Sa expression is primarily determined by cis-acting elements in or near the Sa gene. Our results show that we have successfully isolated a major rat chromosome 1 blood pressure QTL located in the vicinity of the Sa gene in reciprocal congenic strains derived from SHR and WKY. The strains can now be used to further define the region containing the QTL and also to characterize intermediary mechanisms through which the QTL influences blood pressure. In addition, comparison of the regions introgressed in our congenic strains with the location of the peak LOD score for chromosome 1 blood pressure QTL in second filial generation progeny derived from our SHRxWKY cross suggests that there may be at least 1 further QTL influencing blood pressure on this rat chromosome.

Animals↗
PubMedDate not supplied

[Conjugation of the 1BL/1RS translocation with qualitative and quantitative traits in the common wheat T.aestivum].

The review considers the effect of the rye 1BL/1RS translocation in the common wheat genome on qualitative and quantitative traits: grain quality, resistance to diseases, productivity and adaptivity, parthenogenesis, regeneration in anther culture, frequency of chromosome aberrations and frequency of cross-pollination. Data on special features of transmission of the 1BL/1RS translocation through male and female gametes are presented.

Crops, Agricultural↗
PubMed2002

Application of the false discovery rate to quantitative trait loci interval mapping with multiple traits.

Controlling the false discovery rate (FDR) has been proposed as an alternative to controlling the genome-wise error rate (GWER) for detecting quantitative trait loci (QTL) in genome scans. The objective here was to implement FDR in the context of regression interval mapping for multiple traits. Data on five traits from an F2 swine breed cross were used. FDR was implemented using tests at every 1 cM (FDR1) and using tests with the highest test statistic for each marker interval (FDRm). For the latter, a method was developed to predict comparison-wise error rates. At low error rates, FDR1 behaved erratically; FDRm was more stable but gave similar significance thresholds and number of QTL detected. At the same error rate, methods to control FDR gave less stringent significance thresholds and more QTL detected than methods to control GWER. Although testing across traits had limited impact on FDR, single-trait testing was recommended because there is no theoretical reason to pool tests across traits for FDR. FDR based on FDRm was recommended for QTL detection in interval mapping because it provides significance tests that are meaningful, yet not overly stringent, such that a more complete picture of QTL is revealed.

Animals↗
PubMed1999

A search for quantitative trait loci for milk production traits on chromosome 6 in Finnish Ayrshire cattle.

Cattle chromosome 6 was scanned with 11 markers, ten microsatellites and the casein haplotype, to identify quantitative trait loci (QTLs) affecting the following milk production traits: milk yield, fat percentage, fat yield, protein percentage and protein yield. Twelve Finnish Ayrshire half-sib families with a total of 480 sons were genotyped and used in a grand-daughter design. Interval mapping was performed with a multiple-marker regression approach with a one-QTL and a two-QTL model, and the significance threshold values were determined empirically using a permutation test. Across-family analysis with the one-QTL model revealed an effect on protein percentage (P < 0.05) and on milk yield (P < 0.05). The analysis with the two-QTL model identified significant effects (P < 0.05) on protein percentage, milk yield, and fat yield. Comparing these two cases, the results suggest the existence of two QTLs on chromosome 6 with an effect on milk production traits. One of the QTLs was located around the casein genes. As the other QTL was similar in location and effect to a QTL found previously in Holstein-Friesians, an identity-by-descent approach could be applied to fine map this region.

Animals↗
PubMed1998

Mapping quantitative trait loci for carcass and meat quality traits in a wild boar x Large White intercross.

An intercross between wild boar and a domestic Large White pig population was used to map quantitative trait loci (QTL) for body proportions, weight of internal organs, carcass composition, and meat quality. The results concerning growth traits and fat deposition traits have been reported elsewhere. In the present study, all 200 F2 animals, their parents, and their grandparents were genotyped for 236 markers. The marker genotypes were used to calculate the additive and dominance coefficients at fixed positions in the genome of each F2 animal, and the trait values were regressed onto these coefficients in intervals of 1 cM. In addition, the effect of proportion of wild boar alleles was tested for each chromosome. Significant QTL effects were found for percentage lean meat and percentage lean meat plus bone in various cuts, proportion of bone in relation to lean meat in ham, muscle area, and carcass length. The significant QTL were located on chromosomes 2, 3, 4, and 8. Each QTL explained 9 to 16% of the residual variance of the traits. Gene action for most QTL was largely additive. For meat quality traits, there were no QTL that reached the significance threshold. However, the average proportion of wild boar alleles across the genome had highly significant effects on reflectance and drip loss. The results show that there are several chromosome regions with a considerable effect on carcass traits in pigs.

Animals↗