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At least 685 records · Page 38Linked to original sources
PubMed2006

Improved power offered by a score test for linkage disequilibrium mapping of quantitative-trait loci by selective genotyping.

Selective genotyping is used to increase efficiency in genetic association studies of quantitative traits by genotyping only those individuals who deviate from the population mean. However, selection distorts the conditional distribution of the trait given genotype, and such data sets are usually analyzed using case-control methods, quantitative analysis within selected groups, or a combination of both. We show that Hotelling's T(2) test, recently proposed for association studies of one or several tagging single-nucleotide polymorphisms in a prospective (i.e., trait given genotype) design, can also be applied to the retrospective (i.e., genotype given trait) selective-genotyping design, and we use simulation to demonstrate its improved power over existing methods.

Data Interpretation, Statistical↗
PubMedDate not supplied

Testing mode of inheritance of a candidate mutation at a quantitative trait locus.

Here is presented an approach to testing whether the effect of a candidate gene on a quantitative trait is dominant and for testing whether the effect is recessive. The approach uses parental genotype information in nuclear families to adjust for bias due to population admixture. The approach is applicable regardless of the nature of the sampling. The results of an application of the methods to a candidate mutation for diabetic nephropathy are used for illustration.

Diabetes Mellitus, Type 1↗
PubMed2002

Detection of pleiotropic effects of quantitative trait loci in outbred populations using regression analysis.

In this paper a method is presented to determine pleiotropic quantitative trait loci (QTL) or closely linked QTL in an outbred population. The method is based on results from single-trait analyses for different traits and is derived for a granddaughter design. The covariance between estimated contrasts of grandsires obtained in single-trait regression analysis is computed. When there is no pleiotropic QTL, the covariance between contrasts depends on the heritabilities of the traits involved, the polygenic and environmental correlation between the traits, the phenotypic standard deviations, the number of sires per grandsire, and the number of daughters per sire. A pleiotropic QTL results in a covariance that deviates from this expected covariance. The deviation depends on the size of the effects on both traits and on the fraction of grandsires heterozygous for the QTL. When analyzing experimental data, the expected covariance and the confidence interval for the expected covariance can be determined by permutation of the data. A covariance outside the confidence interval suggests the presence of a pleiotropic QTL or a closely linked QTL. The method is verified by simulation and illustrated by analyzing an experimental data set on chromosome 6 in dairy cattle.

Animals↗
PubMed2004

Maximizing genetic gain over multiple generations with quantitative trait locus selection and control of inbreeding.

Stochastic computer simulation was used to investigate the potential extra genetic gains obtained from gene-assisted selection (GAS) by combining 1) optimization of genetic contributions for maximizing gain, while restricting the rate of inbreeding with 2) optimization of the relative emphasis given to the QTL over generations. The genetic model assumed implied a mixed inheritance model in which a single quantitative trait locus (i.e., QTL) is segregating together with polygenes. When compared with standard GAS (i.e., fixed contributions and equal emphasis on the QTL and polygenic EBV), combined optimization of contributions of selection candidates and weights on the QTL across generations allowed substantial increases in gain at a fixed rate of inbreeding and avoided the conflict between short- and long-term responses in GAS schemes. Most of the increase of gain was produced by optimization of selection candidates' contributions. Optimization of the relative emphasis given to the QTL over generations had, however, a greater effect on avoiding the long-term loss usually observed in GAS schemes. Optimized contribution schemes led to lower gametic phase disequilibrium between the QTL and polygenes and to higher selection intensities both on the QTL and polygenes than with standard truncation selection with fixed contributions of selection candidates.

Alleles↗
PubMed2004

Mapping quantitative trait loci for anxiety in chromosome substitution strains of mice.

Anxious behavior in the mouse is a complex quantitative phenotype that varies widely among inbred mouse strains. We examined a panel of chromosome substitution strains bearing individual A/J chromosomes in an otherwise C57BL/6J background in open-field and light-dark transition tests. Our results confirmed previous reports of quantitative trait loci (QTL) on chromosomes 1, 4, and 15 and identified novel loci on chromosomes 6 and 17. The studies were replicated in two separate laboratories. Systematic differences in the overall activity level were found between the two facilities, but the presence of the QTL was confirmed in both laboratories. We also identified specific effects on open-field defecation and center avoidance and distinguished them from overall open-field activity.

Animals↗
PubMed2005

Weighting by heritability for detection of quantitative trait loci with microarray estimates of gene expression.

Heritable differences in transcribed RNA levels can be mapped as quantitative trait loci (QTLs). Transcribed RNA levels are often measured by hybridization to microarrays of oligonucleotide probes, in which each transcript is represented by multiple probes. The use of recombinant inbred lines allows an estimate of the heritability of expression measured by individual probes. This heritability varies greatly. We have tested heritability-weighted averages to define expression of a transcript and found that these allow detection of more QTLs than previously described methods.

Animals↗
PubMedDate not supplied

A further look at quantitative trait loci affecting growth and fatness in a cross between Meishan and Large White pig populations.

A detailed quantitative trait locus (QTL) analysis of growth and fatness data from a three generation experimental cross between Large White (LW) and Meishan (MS) pig breeds was carried out to search for sex x QTL interactions, imprinting effects and multiple linked QTLs. A total of 530 F(2) males and 573 F(2) females issued from 6 F(1) boars and 23 F(1) sows were typed for a total of 137 markers covering the entire porcine genome. Nine growth traits and three backfat thickness measurements were analysed. All analyses were performed using line cross regression procedures. A QTL with sex-specific expression was revealed in the proximal region of chromosome 8, although some confusion between herd and sex effects could not be discarded. This previously undetected QTL affected male growth during the fattening period, with a favourable additive effect of the LW allele. The analyses also revealed the presence of two linked QTLs segregating on chromosome 1, affecting growth traits during the post-weaning period. The first QTL, previously detected using a single QTL model, was located at the end of the q arm of chromosome 1 and had a favourable MS allele. The second QTL had a favourable LW allele and was located in the proximal extremity of the q arm of chromosome 1. Suggestive genomic imprinting was found in the distal region of chromosome 9 affecting growth during the fattening period.

Adipose Tissue↗
PubMed2004

A unified Markov chain Monte Carlo framework for mapping multiple quantitative trait loci.

In this article, a unified Markov chain Monte Carlo (MCMC) framework is proposed to identify multiple quantitative trait loci (QTL) for complex traits in experimental designs, based on a composite space representation of the problem that has fixed dimension. The proposed unified approach includes the existing Bayesian QTL mapping methods using reversible jump MCMC algorithm as special cases. We also show that a variety of Bayesian variable selection methods using Gibbs sampling can be applied to the composite model space for mapping multiple QTL. The unified framework not only results in some new algorithms, but also gives useful insight into some of the important factors governing the performance of Gibbs sampling and reversible jump for mapping multiple QTL. Finally, we develop strategies to improve the performance of MCMC algorithms.

Chromosome Mapping↗
PubMed1997

Sequential sib-pair and association studies to detect genes in quantitative traits.

We applied sib-pair and association methods to a GAW data set of nuclear families with quantitative traits. Our approaches included 1) preliminary statistical studies including correlations and linear regressions, 2) sib-pair methods, and 3) association studies. We used a single data set to screen for linkage and association and, subsequently, additional data sets to confirm the preliminary results. Using this sequential approach, sib-pair analysis provided evidence for the genes influencing Q1, Q2, and Q4. We correctly predicted MG1 for Q1, MG2 for Q2, and MG4 for Q4. We did not find any false positives using this approach. Association studies identified chromosomes 8 and 9 to be associated with Q4; however these are assumed to be false positives as no associations were modeled into the data.

Analysis of Variance↗
PubMed2005

Mapping quantitative trait loci controlling agronomic traits in the spring wheat cross RL4452x'AC Domain'.

Relatively little is known about the genetic control of agronomic traits in common wheat (Triticum aestivum L.) compared with traits that follow Mendelian segregation patterns. A doubled-haploid population was generated from the cross RL4452x'AC Domain' to study the inheritance of the agronomic traits: plant height, time to maturity, lodging, grain yield, test weight, and 1000-grain weight. This cross includes the genetics of 2 western Canadian wheat marketing classes. Composite interval mapping was conducted with a microsatellite linkage map, incorporating 369 loci, and phenotypic data from multiple Manitoba environments. The plant height quantitative trait loci (QTLs), QHt.crc-4B and QHt.crc-4D, mapped to the expected locations of Rht-B1 and Rht-D1. These QTLs were responsible for most of the variation in plant height and were associated with other agronomic traits. An additional 25 agronomic QTLs were detected in the RL4452x'AC Domain' population beyond those associated with QHt.crc-4B and QHt.crc-4D. 'AC Domain' contributed 4 alleles for early maturity, including a major time to maturity QTL on 7D. RL4452 contributed 2 major alleles for increased grain yield at QYld.crc-2B and QYld.crc-4A, which are potential targets for marker-assisted selection. A key test weight QTL was detected on 3B and prominent 1000-grain weight QTLs were identified on 3D and 4A.

Chromosome Mapping↗
PubMed2003

Distribution of temperature tolerance quantitative trait loci in Arctic charr (Salvelinus alpinus) and inferred homologies in rainbow trout (Oncorhynchus mykiss).

We searched for quantitative trait loci (QTL) affecting upper temperature tolerance (UTT) in crosses between the Nauyuk Lake and Fraser River strains of Arctic charr (Salvelinus alpinus) using survival analysis. Two QTL were detected by using two microsatellite markers after correcting for experiment-wide error. A comparative mapping approach localized these two QTL to homologous linkage groups containing UTT QTL in rainbow trout (Oncorhynchus mykiss). Additional marginal associations were detected in several families in regions homologous to those with QTL in rainbow trout. Thus, the genes underlying UTT QTL may antedate the divergence of these two species, which occurred by approximately 16 MYA. The data also indicate that one pair of homeologs (ancestrally duplicated chromosomal segments) have contained QTL in Arctic charr since the evolution of salmonids from a tetraploid ancestor 25-100 MYA. This study represents one of the first examples of comparative QTL mapping in an animal polyploid group and illustrates the fate of QTL after genome duplication and reorganization.

Adaptation, Physiological↗
PubMed1999

Bone marrow pre-B-1 (Bomb1): a quantitative trait locus inducing bone marrow pre-B-cell expansion in lymphoma-prone SL/Kh mice.

Abnormalities of regulatory genes in early B-cell development often lead to lymphomagenesis. Our previous study showed that there is an abnormal transient expansion of bone marrow (BM) pre-B cells in lymphoma-prone SL/Kh strain mice. Such expansion is a genetic property of SL/Kh stem cells rather than BM microenvironments. Using the percentage of BP1+ B220+ pre-B cells in total BM lymphoid cells as a quantitative parameter, we studied the genetic control of BM pre-B cells in 159 F2 offspring of crosses between SL/Kh and NFS/N mice and 334 back-crosses to SL/Kh mice. A highly significant quantitative trait locus was identified on the distal segment of chromosome 3, showing logarithm of odds scores of 22.7 in the F2 cohort and 10.7 in back-cross mice. This quantitative trait locus, named bone marrow pre-B-1, colocalized with lymphoid enhancer factor-1, which encodes a high mobility group DNA-binding protein that is expressed in T and pre-B cells.

Animals↗
PubMed2026

Tonsillar expression quantitative trait loci verify and expand genetic contributors to childhood atopic diseases.

BACKGROUND: The spectrum of causal variants, mechanisms, and immunologic gene networks that influence pediatric atopic traits is not completely understood. Human genetic variation associated with transcript abundance (expression quantitative trait loci [eQTLs]) can help to advance our understanding, yet prior work has focused on profiling immune cell populations collected from peripheral blood primarily in adult populations, leaving tissue-resident lymphocytes collected from children uncharacterized. OBJECTIVE: We sought to characterize gene expression of 4 populations of tonsil-derived immune cell types collected from pediatric patients. METHODS: We collected naive B, germinal center B, naive T, and T follicular helper cells from the discarded tonsils of 103 children across development (age range 1-19). Following genotyping and RNA sequencing of samples, we performed differential expression and eQTL analysis, then statistically linked eQTL signals to relevant atopic traits via colocalization. RESULTS: We found differentially expressed genes across cell types and identified 13,393 expression genes (eGenes) (1,793 eGenes not previously reported in similar datasets) influenced by 27,603 eQTLs (5,199 eQTLs not previously reported). We linked eQTLs to associations identified in pediatric and adult asthma and atopy traits, nominating 78 eGenes including TRAF3, ZBTB10, and JAZF1 in disease-relevant cell types. CONCLUSIONS: Our freely available resource exemplifies the importance of discovery in native tissues and across human development.

Expression quantitative trait locus↗
PubMed2001

Quantitative trait locus analysis in crosses between outbred lines with dominance and inbreeding.

We provide a theoretical framework for quantitative trait locus (QTL) analysis of a crossed population where parental lines may be outbred and dominance as well as inbreeding are allowed for. It can be applied to any pedigree. A biallelic QTL is assumed, and the QTL allele frequencies can be different in each breed. The genetic covariance between any two individuals is expressed as a nonlinear function of the probability of up to 15 possible identity modes and of the additive and dominance effects, together with the allelic frequencies in each of the two parental breeds. The probabilities of each identity mode are obtained at the desired genome positions using a Monte Carlo Markov chain method. Unbiased estimates of the actual genetic parameters are recovered in a simulated F(2) cross and in a six-generation complex pedigree under a variety of genetic models (allele fixed or segregating in the parental populations and additive or dominance action). Results from analyzing an F(2) cross between Meishan and Large White pigs are also presented.

Alleles↗
PubMed2003

Detection of quantitative trait loci for growth and carcass composition in cattle.

The objective of the present study was to detect quantitative trait loci for economically important traits in a family from a Bos indicus x Bos taurus sire. A Brahman x Hereford sire was used to develop a half-sib family (n = 547). The sire was mated to Bos taurus cows. Traits analyzed were birth (kg) and weaning weights (kg); hot carcass weight (kg); marbling score; longissimus area (cm2); USDA yield grade; estimated kidney, pelvic, and heart fat (%); fat thickness (cm); fat yield (%); and retail product yield (%). Meat tenderness was measured as Warner-Bratzler shear force (kg) at 3 and 14 d postmortem. Two hundred and thirty-eight markers were genotyped in 185 offspring. One hundred and thirty markers were used to genotype the remaining 362 offspring. A total of 312 markers were used in the final analysis. Seventy-four markers were common to both groups. Significant QTL (expected number of false-positives < 0.05) were observed for birth weight and longissimus area on chromosome 5, for longissimus area on chromosome 6, for retail product yield on chromosome 9, for birth weight on chromosome 21, and for marbling score on chromosome 23. Evidence suggesting (expected number of false-positives < 1) the presence of QTL was detected for several traits. Putative QTL for birth weight were detected on chromosomes 1, 2, and 3, and for weaning weight on chromosome 29. For hot carcass weight, QTL were detected on chromosomes 10, 18, and 29. Four QTL for yield grade were identified on chromosomes 2, 11, 14, and 19. Three QTL for fat thickness were detected on chromosomes 2, 3, 7, and 14. For marbling score, QTL were identified on chromosomes 3, 10, 14, and 27. Four QTL were identified for retail product yield on chromosomes 12, 18, 19, and 29. A QTL for estimated kidney, pelvic, and heart fat was detected on chromosome 15, and a QTL for meat tenderness measured as Warner-Bratzler shear force at 3 d postmortem was identified on chromosome 20. Two QTL were detected for meat tenderness measured as Warner-Bratzler shear force at 14 d postmortem on chromosomes 20 and 29. These results present a complete scan in all available progeny in this family. Regions underlying QTL need to be assessed in other populations.

Animals↗
PubMed2006

Quantitative trait loci mapping for fatty acid composition traits in perirenal and back fat using a Japanese wild boar x Large White intercross.

Here, we analysed quantitative trait loci (QTL) for fatty acid composition, one of the factors affecting fat quality, in a Japanese wild boar x Large White cross. We found 25 significant effects for 17 traits at 13 positions at the 5% genome-wise level, of which 16 effects for 12 traits at 10 positions were significant at the 1% level. QTL for saturated fatty acids (SFA) in back fat were mapped to swine (Sus scrofa) chromosomes (SSC) 1p, 9 and 15. QTL for unsaturated fatty acids in back fat were mapped to SSC1p, 1q, 4, 5, 9, 15 and 17. Using a regression model that fits back fat thickness as a covariate, two of the QTL for linoleic acid content on SSC4 and SSC17 were not significant, but one QTL for total SFA composition was detected on SSC5 with correction for back fat thickness. Wild boar alleles at six of seven QTL tended to increase SFAs and to decrease unsaturated fatty acids. QTL for fatty acid composition in perirenal fat were mapped on SSC2, 3, 4, 5, 6, 14, 16 and X. QTL for melting point (in back fat samples) were mapped on SSC1, 2 and 15. Wild boar alleles in QTL on SSC1 and SSC15 were associated with elevated melting points whereas those on SSC2 were associated with lower melting point measurements.

Adipose Tissue↗
PubMed2000

Framework for identifying quantitative trait loci in association studies using structural equation modeling.

In this article, we suggest a framework for identifying quantitative trait loci (QTL) in association studies using structural equation modeling. Two tests to detect QTLs and estimate the proportion of variance they explain are discussed. The first test assumes that there is no population admixture and only requires that the subjects are genotyped. The second one is a TDT-like test that cannot give false-positive results due to population admixture but requires that the parents of the subjects are genotyped as well and that subjects have at least one heterozygous parent. Power calculations showed that with the first test, 100 subjects were generally sufficient to detect a locus that explained 10% and less than 1,000 subject to detect a locus that explained 1% of the total variance. To obtain the same power, the TDT-like test required an initial sample that was on average 1.7 times larger. Calculations showed that the first test was quite robust against population admixture and that the power of tests to detect admixture was good. This suggested that in the extreme and very specific conditions in which population admixture may cause false-positive findings, admixture can often be detected.

Alleles↗
PubMed2002

Leaf stomatal and epidermal cell development: identification of putative quantitative trait loci in relation to elevated carbon dioxide concentration in poplar.

Genetic variation in stomatal initiation and density, and epidermal cell size and number were examined in a hybrid pedigree of Populus trichocarpa T. & G. and P. deltoides Marsh in both ambient ([aCO2]) and elevated ([eCO2]) concentrations of CO2. We aimed to link anatomical traits with the underlying genetic map of F2 Family 331, composed of 350 markers across 19 linkage groups. Leaf stomatal and epidermal cell traits showed pronounced differences between the original parents. We considered the following traits in the F2 population: stomatal density (SD), stomatal index (SI), epidermal cell area (ECA) and the number of epidermal cells per leaf (ECN). In [eCO2], adaxial SD and SI were reduced in the F2 population, whereas ECA increased and ECN remained unchanged. In [aCO2], four putative quantitative trait loci (QTL) with logarithm of the odds ratio (LOD) scores greater than 2.9 were found for stomatal traits on linkage group B: adaxial SI (LOD scores of 5.4 and 5.2); abaxial SI (LOD score of 3.3); and SD (LOD score of 3.2). These results imply that QTL for SI and SD share linkage group B and are under genetic control. More moderate LOD scores (LOD scores >/= 2.5) suggest QTL for SI on linkage groups A and B and for SD on linkage groups B, D and X with a probable co-locating quantitative trait locus for SI and SD on linkage group D (position 46.3 cM). The QTL in both [aCO2] and [eCO2] for adaxial SD were co-located on linkage group X (LOD scores of 3.5 and 2.6, respectively) indicating a similar response across both treatments. Putative QTL were located on linkage group A (position 89.2 cM) for both leaf size and ECN in [aCO2] and for ECA at almost the same position. The data provide preliminary evidence that leaf stomatal and cell traits are amenable to QTL analysis.

Carbon Dioxide↗