SEARCH · PubMed Health

Results for “QTL”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8Linked to original sources

PubMed2000

Different functions of QTL for estrogen-dependent tumor growth of the rat pituitary.

Estrogen treatment to rats of the Fischer 344 (F344) strain induces growth of pituitary tumors that exhibit accelerated cell proliferation, breakdown of basement membrane, and formation of hemorrhagic lakes. Estrogen-dependent pituitary growth is due to variation in a group of quantitative trait loci (QTL), called Edpm for estrogen-dependent pituitary mass, that we previously identified in an F(2) intercross of F344 and the tumor-resistant Brown Norway strain. We previously identified 5 QTL, and microsatellite markers developed since our earlier work have allowed us to scan new chromosomal regions, resulting in two new QTL for estrogen-dependent pituitary mass: Edpm9-2 and a possible QTL on the X Chromosome (Chr). Here we report evidence that these QTL differ from each other in how they affect growth. To examine the effect of the Edpm QTL on biochemical components of tumor growth, we tested their effects in 138 progeny of a backcross to the F344 strain which were given a 10-week chronic estrogen treatment. Hemoglobin/DNA ratio (a measure of blood volume relative to cell number) and total pituitary DNA (a measure of cell number) correlated only weakly, and very large pituitaries were observed which had a low hemoglobin/DNA ratio resembling a normal gland. Through QTL mapping, we found that Edpm2-1, Edpm3, Edpm5, and Edpm9-2 all had significant effects on pituitary mass, but Edpm2-1 and Edpm9-2 primarily affected DNA content, Edpm5 primarily affected hemoglobin/DNA ratio, and Edpm3 affected all traits equally.

Animals↗

PubMed2001

Detection of QTL for milk production on Chromosomes 1 and 6 of Holstein cattle.

Seventy to 75 sons of each of six Holstein sires were assayed for genotypes at a number of microsatellite loci spanning Chromosomes (Chrs) 1 and 6. The number of informative loci varied from three to eight on each chromosome in different sire families. Linkage order and map distance for microsatellite loci were estimated using CRI-MAP. Estimates of QTL effect and location were made by using a least squares interval mapping approach based on daughter yield deviations of sons for 305-d milk, fat, protein yield, and fat and protein percentage. Thresholds for statistical significance of QTL effects were determined from interval mapping of 10,000 random permutations of the data across the bull sire families and within each sire family separately. Across-sire analyses indicated a significant QTL for fat and protein yield, and fat percentage on Chr 1, and QTL effects on milk yield and protein percentage that might represent one or two QTL on Chr 6. Analyses within each sire family indicated significant QTL effects in five sire families, with one sire possibly being heterozygous for two QTLs. Statistically significant estimates of QTL effects on breeding value ranged from 340 to 640 kg of milk, from 15.6 to 28.4 kg of fat, and 14.4 to 17.6 kg of protein.

Alleles↗

PubMed2006

Improving QTL mapping resolution based on genotypic sampling--a case using a RIL population.

The QTL mapping results were compared with the genotypically selected and random samples of the same size on the base of a RIL population. The results demonstrated that there were no obvious differences in the trait distribution and marker segregation distortion between the genotypically selected and random samples with the same population size. However, a significant increase in QTL detection power, sensitivity, specificity, and QTL resolution in the genotypically selected samples were observed. Moreover, the highly significant effect was detected in small size of genotypically selected samples. In QTL mapping, phenotyping is a more sensitive limiting factor than genotyping so that the selection of samples could be an attractive strategy for increasing genome-wide QTL mapping resolution. The efficient selection of samples should be more helpful for QTL maker assistant selection, fine mapping, and QTL cloning.

Chromosome Mapping↗

PubMed2005

Evaluation of linkage disequilibrium measures between multi-allelic markers as predictors of linkage disequilibrium between markers and QTL.

Effectiveness of marker-assisted selection (MAS) and quantitative trait loci (QTL) mapping using population-wide linkage disequilibrium (LD) between markers and QTL depends on the extent of LD and how it declines with distance in a population. Because marker-QTL LD cannot be observed directly, the objective of this study was to evaluate alternative measures of observable LD between multi-allelic markers as predictors of usable LD of multi-allelic markers with presumed biallelic QTL. Observable LD between marker pairs was evaluated using eight existing measures and one new measure. These consisted of two pooled and standardized measures of LD between pairs of alleles at two markers based on Lewontin's LD measure, two pooled measures of squared correlations between alleles, one standardized measure using Hardy-Weinberg heterozygosities, and four measures based on the chi-square statistic for testing for association between alleles at two loci. In simulated populations with a range of LD generated by drift and a range of marker polymorphism, marker-marker LD measured by a standardized chi-square statistic (denoted chi(2')) was found to be the best predictor of useable marker-QTL LD for a group of multi-allelic markers. Estimates of the level and decline of marker-marker LD with distance obtained from chi(2') were linearly and highly correlated with usable LD of those markers with QTL across population structures and marker polymorphism. Corresponding relationships were poorer for the other marker-marker LD measures. Therefore, when LD is generated by drift, chi(2') is recommended to quantify the amount and extent of usable LD in a population for QTL mapping and MAS based on multi-allelic markers.

Alleles↗

PubMed1997

A simple method to calculate resolving power and confidence interval of QTL map location.

"Resolving power" is defined as the 95% confidence interval for quantitative trait locus (QTL) map location that would be obtained when scoring an infinite number of markers in a given constellation of a marker-QTL mapping experiment. Resolving power can serve as a close estimate of the confidence interval of QTL map location, as well as a guide to the lower efficient limit of marker spacing in an initial marker-QTL mapping experiment. In the present study, an extensive series of simulations was carried out to provide estimates of resolving power, for backcross (BC) and F2 designs, over a wide range of experimental sizes and of gene effects and dominance at the QTL. From the simulation results, the remarkably simple expressions, 3000/(mNd2) (where m = 1 for BC and m = 2 for F2; N = population size, and d = allele substitution effect) and 530/Nv (in terms of v, the proportion of variance explained), were obtained for estimating resolving power. These expressions can provide a convenient guide to planning marker spacing in BC and F2 marker-QTL linkage experiments and for placing confidence intervals about QTL map location obtained in such experiments.

Animals↗

PubMed2005

QTL for body weight and condition factor in Atlantic salmon (Salmo salar): comparative analysis with rainbow trout (Oncorhynchus mykiss) and Arctic charr (Salvelinus alpinus).

Genotypes at 91 microsatellite loci in three full-sib families were used to search for QTL affecting body weight (BW) and condition factor in North American Atlantic salmon (Salmo salar). More than one informative marker was identified on 16-18 linkage groups in each family, allowing at least one chromosomal interval to be analyzed per linkage group. Two significant QTL for BW on linkage groups AS-8 and AS-11, and four significant QTL for condition factor on linkage groups AS-2, AS-5, AS-11, and AS-14 were identified. QTL for both BW and condition factor were located on linkage groups AS-1, 6, 8, 11, and 14 when considering both significant and suggestive QTL effects. The largest QTL effects for BW (AS-8) and for condition factor (AS-14) accounted for 20.1 and 24.9% of the trait variation, respectively. Three of the QTL for BW occur on linkage groups where similar effects have been detected on the homologous regions in either rainbow trout (Oncorhynchus mykiss) or Arctic charr (Salvelinus alpinus).

Animals↗

PubMed2006

Using mating designs to uncover QTL and the genetic architecture of complex traits.

Analysis of quantitative trait loci (QTL) affecting complex traits is often pursued in single-cross experiments. For most purposes, including breeding, some assessment is desired of the generalizability of the QTL findings and of the overall genetic architecture of the trait. Single-cross experiments provide a poor basis for these purposes, as comparison across experiments is hampered by segregation of different allelic combinations among different parents and by context-dependent effects of QTL. To overcome this problem, we combined the benefits of QTL analysis (to identify genomic regions affecting trait variation) and classic diallel analysis (to obtain insight into the general inheritance of the trait) by analyzing multiple mapping families that are connected via shared parents. We first provide a theoretical derivation of main (general combining ability (GCA)) and interaction (specific combining ability (SCA)) effects on F(2) family means relative to variance components in a randomly mating reference population. Then, using computer simulations to generate F(2) families derived from 10 inbred parents in different partial-diallel designs, we show that QTL can be detected and that the residual among-family variance can be analyzed. Standard diallel analysis methods are applied in order to reveal the presence and mode of action (in terms of GCA and SCA) of undetected polygenes. Given a fixed experiment size (total number of individuals), we demonstrate that QTL detection and estimation of the genetic architecture of polygenic effects are competing goals, which should be explicitly accounted for in the experimental design. Our approach provides a general strategy for exploring the genetic architecture, as well as the QTL underlying variation in quantitative traits.

Animals↗

PubMed2003

Molecular genetics of submergence tolerance in rice: QTL analysis of key traits.

Flash flooding of young rice plants is a common problem for rice farmers in south and south-east Asia. It severely reduces grain yield and increases the unpredictability of cropping. The inheritance and expression of traits associated with submergence stress tolerance at the seedling stage are physiologically and genetically complex. We exploited naturally occurring differences between certain rice lines in their tolerance to submergence and used quantitative trait loci (QTL) mapping to improve understanding of the genetic and physiological basis of submergence tolerance. Three rice populations, each derived from a single cross between two cultivars differing in their response to submergence, were used to identify QTL associated with plant survival and various linked traits. These included total shoot elongation under water, the extent of stimulation of shoot elongation caused by submergence, a visual submergence tolerance score, and leaf senescence under different field conditions, locations and years. Several major QTL determining plant survival, plant height, stimulation of shoot elongation, visual tolerance score and leaf senescence each mapped to the same locus on chromosome 9. These QTL were detected consistently in experiments across all years and in the genetic backgrounds of all three mapping populations. Secondary QTL influencing tolerance were also identified and located on chromosomes 1, 2, 5, 7, 10 and 11. These QTL were specific to particular traits, environments, or genetic backgrounds. All identified QTL contributed to increased submergence tolerance through their effects on decreased underwater shoot elongation or increased maintenance of chlorophyll levels, or on both. These findings establish the foundations of a marker-assisted scheme for introducing submergence tolerance into agriculturally desirable cultivars of rice.

Adaptation, Physiological↗

PubMed2003

Mapping of QTL associated with nitrogen storage and remobilization in barley (Hordeum vulgare L.) leaves.

Nitrogen uptake and metabolism are central for vegetative and reproductive plant growth. This is reflected by the fact that nitrogen can be remobilized and reused within a plant, and this process is crucial for yield in most annual crops. A population of 146 recombinant inbred barley lines (F(8) and F(9) plants, grown in 2000 and 2001), derived from a cross between two varieties differing markedly in grain protein concentration, was used to compare the location of QTL associated with nitrogen uptake, storage and remobilization in flag leaves relative to QTL controlling developmental parameters and grain protein accumulation. Overlaps of support intervals for such QTL were found on several chromosomes, with chromosomes 3 and 6 being especially important. For QTL on these chromosomes, alleles associated with inefficient N remobilization were associated with depressed yield and higher levels of total or soluble organic nitrogen during grain filling and vice versa; therefore, genes directly involved in N recycling or genes regulating N recycling may be located on these chromosomes. Interestingly, the most prominent QTL for grain protein concentration (on chromosome 6) did not co-localize with QTL for nitrogen remobilization. However, QTL peaks for nitrate and soluble organic nitrogen were detected at this locus for plants grown in 2001 (but not in 2000). For these, alleles associated with low grain protein concentration were associated with higher soluble nitrogen levels in leaves during grain filling; therefore, gene(s) found at this locus might influence the nitrogen sink strength of developing barley grains.

Algorithms↗

PubMed2005

Root-ABA1, a major constitutive QTL, affects maize root architecture and leaf ABA concentration at different water regimes.

Near-isogenic hybrids (NIHs), developed from crossing maize (Zea mays L.) backcross-derived lines (BDLs) differing for the parental alleles at a major QTL for leaf ABA concentration (L-ABA), were field-tested for 2 years under well-watered and water-stressed conditions. Differences among NIHs for L-ABA and other morpho-physiological traits were not affected by water regimes. On average, the QTL allele for high L-ABA markedly reduced stomatal conductance and root lodging. To elucidate the effects of the QTL on root architecture and L-ABA, root traits of two pairs of BDLs were measured in plants grown in soil columns at three water regimes. Differences among BDLs were not affected by water regimes. Across water regimes, the QTL confirmed its effect on L-ABA and showed a concurrent effect on root angle, branching, number, diameter, and dry weight. Based on these results, it is concluded that the QTL affects root lodging through a constitutive effect on root architecture. In addition, there is speculation that the QTL effects on root traits and L-ABA are probably due to pleiotropy rather than linkage and a model is proposed in which the QTL has a direct effect on root architecture, while indirectly affecting L-ABA.

Abscisic Acid↗

PubMed2001

Identification of wound healing/regeneration quantitative trait loci (QTL) at multiple time points that explain seventy percent of variance in (MRL/MpJ and SJL/J) mice F2 population.

Studies on genetic mechanisms of wound healing in mammals are very few, although injury is a leading cause of the global burden of disease. In this study, we performed a high-density, genome-wide scan using 633 (MRL/MPJ x SJL/J) F(2) intercross at multiple time points (days 15, 21, and 25) to identify quantitative trait loci (QTL) involved in wound healing/regeneration. The hypothesis of the study was that QTL and unique epistatic interactions are involved at each time point to promote wound healing/regeneration. Ten QTL were identified from chromosomes 1, 4, 6, 7, 9, and 13. Of the 10 QTL, eight from chromosomes 1, 4, 6, and 9 were novel as compared to QTL identified in the study. The 10 QTL altogether explained 70% of variance in F(2) mice. The same QTL were identified at each time point, with simple linear correlation between days 15, 21, and 25, showing very high significant relationships (R >0.92, P <0.0001). Unique epistatic interactions were identified at each time point except those from chromosomes 4, 6, 9, and 13 that were found at all three time points, showing that some loci are involved at all the three time points of wound healing (days 15, 21, and 25). Therefore, loci-to-loci interactions may play a major role in wound healing. Information from these studies may help in the identification of genes that could be involved in wound healing/regeneration.

Analysis of Variance↗

PubMed1998

Genome scan and congenic strains for blood pressure QTL using Dahl salt-sensitive rats.

An F2 population (n = 151) derived from Dahl salt-sensitive (S) and Lewis rats was raised on a 8% NaCl diet for 9 weeks and analyzed for blood pressure quantitative trait loci (QTL) by use of a whole genome scan. Chromosomes 5 and 10 yielded lod scores for linkage to blood pressure that were significant; chromosomes 1, 2, 3, 8, 16, 17, and 18 gave lod scores suggestive for linkage. Chromosome 7 gave a significant signal for heart weight with a lesser effect on blood pressure. Congenic strains were constructed by introgressing Lewis low-blood-pressure QTL alleles for chromosomes 1, 5, 10, and 17 into the S genetic background. Congenic strains for chromosomes 1, 5, and 10 had significantly lower blood pressure than S, proving the existence of QTL on these chromosomes, but the chromosome 17 congenic strain failed to trap a contrasting QTL allele. The QTL allele increasing blood pressure originated from S rats for all QTL except those on chromosomes 2 and 7 in which the Lewis allele increased blood pressure. Interactions between each QTL and every other locus in the genome scan yielded significant interactions between chromosomes 10 and 4, and between chromosomes 2 and 3.

Animals↗

PubMed2005

The value of prior information for detection of QTL affecting longitudinal traits: an example using Von Bertalanffy growth function.

A Bayesian procedure is presented for detecting quantitative trait loci (QTL) affecting longitudinal traits. The statistical model assumes a QTL affecting the prior distribution of the parameters of a given production function, under a hierarchical Bayesian scheme. Marginal posterior distributions for the effects associated with the QTL are calculated using Markov chain Monte Carlo methods. Furthermore, the Bayesian analysis allows the use of some available relevant information that can improve the detection of the QTL substantially. To illustrate the procedure, an example of QTL detection using the Von Bertalanffy growth function is presented with a F2 pig population bred from Iberian boars and Landrace sows. Animals of the F2 population were genotyped for seven markers in chromosome 2 (SSC2). Two prior distributions for the mean effect of the parameters related with birth and adult weight were compared. On the one hand, vague prior distributions were used, and, on the other, there were assumed univariate Gaussian distributions that ensure biologically meaningful adult and birth weights on the posterior growth curves. Results from the second prior distribution supported the presence of QTL, by showing that individuals with both alleles of Iberian origin had lower rates of maturation. On the contrary, when vague priors were used, the procedure was not able to detect QTL.

Animals↗

PubMed2003

Molecular mapping in tropical maize (Zea mays L.) using microsatellite markers. 2. Quantitative trait loci (QTL) for grain yield, plant height, ear height and grain moisture.

A previous genetic map containing 117 microsatellite loci and 400 F(2) plants was used for quantitative trait loci (QTL) mapping in tropical maize. QTL were characterized in a population of 400 F(2:3) lines, derived from selfing the F(2) plants, and were evaluated with two replications in five environments. QTL determinations were made from the mean of these five environments. Grain yield (GY), plant height (PH), ear height (EH) and grain moisture (GM) were measured. Variance components for genotypes (G), environments (E) and GxE interaction were highly significant for all traits. Heritability was 0.69 for GY, 0.66 for PH, 0.67 for EH and 0.23 for GM. Using composite interval mapping (CIM), a total of 13 distinct QTLs were identified: four for GY, four for PH and five for EH. No QTL was detected for GM. The QTL explained 32.73 % of the phenotypic variance of GY, 24.76 % of PH and 20.91 % of EH. The 13 QTLs displayed mostly partial dominance or overdominance gene action and mapped to chromosomes 1, 2, 7, 8 and 9. Most QTL alleles conferring high values for the traits came from line L-14-4B. Mapping analysis identified genomic regions associated with two or more traits in a manner that was consistent with correlation among traits, supporting either pleiotropy or tight linkage among QTL. The low number of QTLs found, can be due to the great variation that exists among tropical environments.

Microsatellite Repeats↗

PubMed2002

Genetic analysis of scab resistance QTL in wheat with microsatellite and AFLP markers.

Three chromosomal regions associated with scab resistance were detected in a common cultivar, Ning7840, by microsatellite and AFLP analysis. Six microsatellites on chromosome 3BS, Xgwm389, Xgwm533, Xbarc147, Xgwm493, Xbarc102, and Xbarc131, were integrated into an amplified fragment length polymorphism (AFLP) linkage group containing a major quantitative trait locus (QTL) for scab resistance in a mapping population of 133 recombinant inbred lines (RILs) derived from 'Ning7840' x 'Clark'. Based on single-factor analysis of variance of scab infection data from four experiments, Xgwm533 and Xbarc147 were the two microsatellite markers most tightly associated with the major scab resistance QTL. Interval analysis based on the integrated map of AFLP and microsatellite markers showed that the major QTL was located in a chromosome region about 8 cM in length around Xgwm533 and Xbarc147. Based on mapping of six microsatellite markers on eight 3BS deletion lines, the major QTL was located distal to breakage point 3BS-8. In total, 18 microsatellites were physically located on different subarm regions on 3BS. Two microsatellites, Xgwm120 and Xgwm614, were significantly associated with QTL for scab resistance on chromosome 2BL and 2AS, respectively. The resistance alleles on 3BS, 2BL, and 2AS were all derived from 'Ning7840'. Significant interaction between the major QTL on 3BS and the QTL on 2BL was detected based on microsatellite markers linked to them. Using these microsatellite markers would facilitate marker-assisted selection to improve scab resistance in wheat.

Chromosome Mapping↗

PubMed2004

Microarray gene expression analysis of the Fob3b obesity QTL identifies positional candidate gene Sqle and perturbed cholesterol and glycolysis pathways.

Obesity-related diseases are poised to become the primary cause of death in developed nations. While a number of monogenic causes of obesity have recently been identified, these are responsible for only a small proportion of human cases of obesity. Quantitative trait locus (QTL) studies using animal models have revealed hundreds of potential loci that affect obesity; however, few have been further analyzed beyond the original QTL scan. We previously mapped four QTL in an F(2) between divergently selected Fat (F) and Lean (L) lines. A QTL of large effect on chromosome 15 (Fob3) was subsequently mapped to a higher resolution into two smaller-effect QTL (Fob3a and Fob3b) using crosses between the F-line and a congenic line containing L-line alleles at the Fob3 QTL region. Here we report the gene expression characterization of Fob3b. Microarray expression analysis using the NIA-NIH 15K cDNA array set containing 14,938 mouse ESTs was employed to identify candidate genes and pathways that are differentially expressed between the F-line and a congenic line containing only the Fob3b QTL (Fob3b-line). Our study suggests squalene epoxidase (Sqle), a cholesterol biosynthesis enzyme, as a strong positional candidate gene for Fob3b. Several other cholesterol biosynthesis pathway genes unlinked to Fob3b were found to be differentially expressed, suggesting that a perturbation of this pathway could be in part responsible for the phenotypic difference between the F-line and Fob3b-line mice.

Animals↗

PubMedDate not supplied

QTL detection and allelic effects for growth and fat traits in outbred pig populations.

Quantitative trait loci (QTL) for growth and fatness traits have previously been identified on chromosomes 4 and 7 in several experimental pig populations. The segregation of these QTL in commercial pigs was studied in a sample of 2713 animals from five different populations. Variance component analysis (VCA) using a marker-based identity by descent (IBD) matrix was applied. The IBD coefficient was estimated with simple deterministic (SMD) and Markov chain Monte Carlo (MCMC) methods. Data for two growth traits, average daily gain on test and whole life daily gain, and back fat thickness were analysed. With both methods, seven out of 26 combinations of population, chromosome and trait, were significant. Additionally, QTL genotypic and allelic effects were estimated when the QTL effect was significant. The range of QTL genotypic effects in a population varied from 4.8% to 10.9% of the phenotypic mean for growth traits and 7.9% to 19.5% for back fat trait. Heritabilities of the QTL genotypic values ranged from 8.6% to 18.2% for growth traits, and 14.5% to 19.2% for back fat. Very similar results were obtained with both SMD and MCMC. However, the MCMC method required a large number of iterations, and hence computation time, especially when the QTL test position was close to the marker.

Animals↗

PubMedDate not supplied

Optimizing purebred selection for crossbred performance using QTL with different degrees of dominance.

A method was developed to optimize simultaneous selection for a quantitative trait with a known QTL within a male and a female line to maximize crossbred performance from a two-way cross. Strategies to maximize cumulative discounted response in crossbred performance over ten generations were derived by optimizing weights in an index of a QTL and phenotype. Strategies were compared to selection on purebred phenotype. Extra responses were limited for QTL with additive and partial dominance effects, but substantial for QTL with over-dominance, for which optimal QTL selection resulted in differential selection in male and female lines to increase the frequency of heterozygotes and polygenic responses. For over-dominant QTL, maximization of crossbred performance one generation at a time resulted in similar responses as optimization across all generations and simultaneous optimal selection in a male and female line resulted in greater response than optimal selection within a single line without crossbreeding. Results show that strategic use of information on over-dominant QTL can enhance crossbred performance without crossbred testing.

Alleles↗