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PubMed2002

Quantitative trait loci for lifespan of mated Drosophila melanogaster affect both sexes.

The properties of alleles at quantitative trait loci (QTLs) contributing to variation in lifespan should be described to determine the mechanisms of evolution of life length and to predict its future changes. Previously, we and others conducted genome-wide screens for QTLs that segregate among one panel of recombinant inbred lines (RILs) using a dense molecular marker map. In non-stressful conditions, QTLs effecting the lifespans of virgin females and males were frequently sex specific. In an unrelated panel of RILs, the effects of QTLs in flies maintained in cages with mixed sexes were similar in both sexes. Here, we re-measured the lifespans of the former panel of RILs in cages with mixed sex cohorts. Lifespan declined owing to mating. The amount of decline correlated between sexes within lines. QTLs mapping to the intervals 15A-19C, 50B-57C, 63A-65A, and 96F-99B had similar effects on the lifespans of both males and females. These QTLs have previously been detected in virgin flies surveys and had sex- and/or environment-specific effects.

Animals↗
PubMed1998

Quantitative trait loci for honey bee stinging behavior and body size.

A study was conducted to identify quantitative trait loci (QTLs) that affect colony-level stinging behavior and individual body size of honey bees. An F1 queen was produced from a cross between a queen of European origin and a drone descended from an African subspecies. Haploid drones from the hybrid queen were individually backcrossed to sister European queens to produce 172 colonies with backcross workers that were evaluated for tendency to sting. Random amplified polymorphic DNA markers were scored from the haploid drone fathers of these colonies. Wings of workers and drones were used as a measure of body size because Africanized bees in the Americas are smaller than European bees. Standard interval mapping and multiple QTL models were used to analyze data. One possible QTL was identified with a significant effect on tendency to sting (LOD 3.57). Four other suggestive QTLs were also observed (about LOD 1.5). Possible QTLs also were identified that affect body size and were unlinked to defensive-behavior QTLs. Two of these were significant (LOD 3.54 and 5.15).

Animals↗
PubMed2007

The quantitative trait gene latexin influences the size of the hematopoietic stem cell population in mice.

We mapped quantitative trait loci that accounted for the variation in hematopoietic stem cell (HSC) numbers between young adult C57BL/6 (B6) and DBA/2 (D2) mice. In reciprocal chromosome 3 congenic mice, introgressed D2 alleles increased HSC numbers owing to enhanced proliferation and self-renewal and reduced apoptosis, whereas B6 alleles had the opposite effects. Using oligonucleotide arrays, real-time PCR and protein blots, we identified latexin (Lxn), a gene whose differential transcription and expression was associated with the allelic differences. Expression was inversely correlated with the number of HSCs; therefore, ectopic expression of Lxn using a retroviral vector decreased stem cell population size. We identified clusters of SNPs upstream of the Lxn transcriptional start site, at least two of which are associated with potential binding sites for transcription factors regulating stem cells. Thus, promoter polymorphisms between the B6 and D2 alleles may affect Lxn gene expression and consequently influence the population size of hematopoietic stem cells.

Animals↗
PubMedDate not supplied

A rapid method for computing the inverse of the gametic covariance matrix between relatives for a marked quantitative trait locus.

The inverse of the gametic covariance matrix between relatives, G(-1), for a marked quantitative trait locus (QTL) is required in best linear unbiased prediction (BLUP) of breeding values if marker data are available on a QTL. A rapid method for computing the inverse of a gametic relationship matrix for a marked QTL without building G itself is presented. The algorithm is particularly useful due to the approach taken in computing inbreeding coefficients by having to compute only few elements of G. Numerical techniques for determining, storing, and computing the required elements of G and the nonzero elements of the inverse are discussed. We show that the subset of G required for computing the inbreeding coefficients and hence the inverse is a tiny proportion of the whole matrix and can be easily stored in computer memory using sparse matrix storage techniques. We also introduce an algorithm to determine the maximum set of nonzero elements that can be found in G(-1) and a strategy to efficiently store and access them. Finally, we demonstrate that the inverse can be efficiently built using the present techniques for very large and inbred populations.

Algorithms↗
PubMed1999

Fine mapping and characterization of linked quantitative trait loci involved in the transition of the maize apical meristem from vegetative to generative structures.

Quantitative trait locus (QTL) mapping has detected two linked QTL in the 8L chromosome arm segment introgressed from Gaspé Flint (a Northern Flint open-pollinated population) into the background of N28 (a Corn Belt Dent inbred line). Homozygous recombinant lines, with a variable length of the introgressed segment, confirmed the presence of the two previously identified, linked QTL. In the N28 background, Gaspé Flint QTL alleles at both loci induce a reduction in node number, height, and days to anthesis (pollen shed). Given the determinate growth pattern of maize, the phenotypic effects indicate that the two QTL are involved in the transition of the apical meristem from vegetative to generative structures. Relative to the effects of the two QTL in the background of N28, we distinguish two general developmental factors affecting the timing of pollen shed. The primary factor is the timing of the transition of the apical meristem. The second, derivative factor is the global extent of internode elongation. Having separated the two linked QTL, we have laid the foundation for the positional cloning of the QTL with a larger effect.

Analysis of Variance↗
PubMed2000

Hd1, a major photoperiod sensitivity quantitative trait locus in rice, is closely related to the Arabidopsis flowering time gene CONSTANS.

A major quantitative trait locus (QTL) controlling response to photoperiod, Hd1, was identified by means of a map-based cloning strategy. High-resolution mapping using 1505 segregants enabled us to define a genomic region of approximately 12 kb as a candidate for Hd1. Further analysis revealed that the Hd1 QTL corresponds to a gene that is a homolog of CONSTANS in Arabidopsis. Sequencing analysis revealed a 43-bp deletion in the first exon of the photoperiod sensitivity 1 (se1) mutant HS66 and a 433-bp insertion in the intron in mutant HS110. Se1 is allelic to the Hd1 QTL, as determined by analysis of two se1 mutants, HS66 and HS110. Genetic complementation analysis proved the function of the candidate gene. The amount of Hd1 mRNA was not greatly affected by a change in length of the photoperiod. We suggest that Hd1 functions in the promotion of heading under short-day conditions and in inhibition under long-day conditions.

Amino Acid Sequence↗
PubMed2006

Multitrait quantitative trait Loci mapping for milk production traits in danish Holstein cattle.

The aims of this study were (1) to confirm previously identified quantitative trait loci (QTL) on bovine chromosomes 6, 11, 14, and 23 in the Danish Holstein cattle population, (2) to assess the pleiotropic nature of each QTL on milk production traits by building multitrait and multi-QTL models, and (3) to include pedigree information on nongenotyped individuals to improve the estimation of genetic parameters underlying the random QTL model. Nineteen grandsire families were analyzed by single-trait (ST) and multitrait (MT) QTL mapping methods. The variance component-based QTL mapping model was implemented via restricted maximum likelihood (REML) to estimate QTL position and parameters. Segregation of the previously identified QTL was confirmed on bovine chromosomes 6, 11, and 14, but not on 23. A highly significant (1% chromosome-wise level) QTL was found on chromosome 6, between 37 and 73 cM. This QTL had a strong effect on protein percentage (PP) and fat percentage (FP) according to ST analyses, and effects on PP, FP, milk yield (MY), fat yield (FY), and protein yield (PY) in MT analyses. A QTL affecting PP was detected on chromosome 11 (at 70 cM) using ST analysis. The MT analysis revealed a second QTL (at 67 cM) approaching significance with an effect on MY. The ST analysis identified a QTL for MY and FP on chromosome 14, between 10 and 24 cM. The extended pedigree (nongenotyped animals) was included to estimate genetic parameters underlying the random QTL model; that is, additive polygenic and QTL variances. In general, the estimates of the QTL variance components were smaller but more precise when the extended pedigree was considered in the analysis.

Animals↗
PubMed2003

Exaggerated response to restraint stress in rats congenic for the chromosome 1 blood pressure quantitative trait locus.

1. To understand the roles of a putative hypertension gene in the chromosome 1 quantitative trait locus (QTL) region, the response to restraint stress was studied in strains congenic for this QTL. 2. To establish congenic strains, the QTL region was introgressed from stroke-prone spontaneously hypertensive rats (SHRSP)/Izm to Wistar-Kyoto/Izm (WKY/Izm) rats by repeated backcrossing. Two congenic strains (WKYpch1.0 and WKYpch1.1) were established to cover the whole QTL region between D1Wox29 and D1Arb21 (approximately 40 cM) and a smaller region between D1Smu11 and D1Arb21 (approximately 10 cM), respectively. After telemetry probes were implanted, rats were exposed to restraint stress to investigate the blood pressure response. 3. Basal blood pressure measured by radiotelemetry differed significantly between WKY rats and WKYpch1.0 (103 +/- 10 and 116 +/- 4 mmHg, respectively; P = 0.002 by anova). When exposed to restraint stress, WKYpch1.0 showed a greater increase in blood pressre than did WKY rats. The exaggerated response in the WKYpch1.0 strain was abolished by chemical sympathectomy using guanethidine. The WKYpch1.1 rats did not differ significantly from WKY rats either in basal blood pressure or in the response to restraint stress. 4. In conclusion, a QTL for high blood pressure was successfully introgressed in the established congenic strain, WKYpch1.0. A gene (or genes) in the chromosome 1 QTL region modulates the cardiovascular responses to restraint stress in these congenic rats, probably through the sympathetic nervous system.

Animals↗
PubMed1998

Quantitative trait loci affecting body weight and fatness from a mouse line selected for extreme high growth.

Quantitative trait loci (QTL) influencing body weight were mapped by linkage analysis in crosses between a high body weight selected line (DU6) and a control line (DUKs). The two mouse lines differ in body weight by 106% and in abdominal fat weight by 100% at 42 days. They were generated from the same base population and maintained as outbred colonies. Determination of line-specific allele frequencies at microsatellite markers spanning the genome indicated significant changes between the lines on 15 autosomes and the X chromosome. To confirm these effects, a QTL analysis was performed using structured F2 pedigrees derived from crosses of a single male from DU6 with a female from DUKs. QTL significant at the genome-wide level were mapped for body weight on chromosome 11; for abdominal fat weight on chromosomes 4, 11, and 13; for abdominal fat percentage on chromosomes 3 and 4; and for the weights of liver on chromosomes 4 and 11, of kidney on chromosomes 2 and 9, and of spleen on chromosome 11. The strong effect on body weight of the QTL on chromosome 11 was confirmed in three independent pedigrees. The effect was additive and independent of sex, accounting for 21-35% of the phenotypic variance of body weight within the corresponding F2 populations. The test for multiple QTL on chromosome 11 with combined data from all pedigrees indicated the segregation of two loci separated by 36 cM influencing body weight.

Alleles↗
PubMed2002

Quantitative trait loci controlling light and hormone response in two accessions of Arabidopsis thaliana.

We have mapped quantitative trait loci (QTL) responsible for natural variation in light and hormone response between the Cape Verde Islands (Cvi) and Landsberg erecta (Ler) accessions of Arabidopsis thaliana using recombinant inbred lines (RILs). Hypocotyl length was measured in four light environments: white, blue, red, and far-red light and in the dark. In addition, white light plus gibberellin (GA) and dark plus the brassinosteroid biosynthesis inhibitor brassinazole (BRZ) were used to detect hormone effects. Twelve QTL were identified that map to loci not previously known to affect light response, as well as loci where candidate genes have been identified from known mutations. Some QTL act in all environments while others show genotype-by-environment interaction. A global threshold was established to identify a significant epistatic interaction between two loci that have few main effects of their own. LIGHT1, a major QTL, has been confirmed in a near isogenic line (NIL) and maps to a new locus with effects in all light environments. The erecta mutation can explain the effect of the HYP2 QTL in the blue, BRZ, and dark environments, but not in far-red. LIGHT2, also confirmed in an NIL, has effects in white and red light and shows interaction with GA. The phenotype and map position of LIGHT2 suggest the photoreceptor PHYB as a candidate gene. Natural variation in light and hormone response thus defines both new genes and known genes that control light response in wild accessions.

Arabidopsis↗
PubMed2006

QTL MatchMaker: a multi-species quantitative trait loci (QTL) database and query system for annotation of genes and QTL.

Identifying genes that underlie quantitative trait loci (QTL) is a challenging task. Here, we present a new QTL software system, named QTL MatchMaker. The system is designed to integrate and mine QTL information across human, mouse and rat genomes and to annotate functional genomic data. It combines and organizes information from relevant public databases and publications and integrates QTL, physical, genetic and cytogenetic maps across human, mouse and rat. To make this application available to the research community we have developed a website for high-throughput mapping of expressed sequences to QTL and for selection of candidate genes in the physiological genomics context of complex traits. QTL MatchMaker is accessible at http://pmrc.med.mssm.edu:9090/QTL/jsp/qtlhome.jsp.

Animals↗
PubMed1994

Ionizing radiation and genetic risks. V. Multifactorial diseases: a review of epidemiological and genetic aspects of congenital abnormalities in man and of models on maintenance of quantitative traits in populations.

This paper discusses (a) data on the epidemiological and etiological aspects of human congenital abnormalities, (b) the multifactorial threshold model and other models which have been proposed to explain their inheritance patterns and recurrence risks in families and (c) current concepts on mechanisms on the prevalence of heritable variation for quantitative traits in populations. Congenital abnormalities, which afflict an estimated 6% of all live births, are etiologically heterogeneous. The majority of these do not follow Mendelian transmission patterns, but do 'run' in families. The multifactorial threshold model is an extension of genetic principles developed for quantitative traits to all-or-none traits; in its simplest formulation, it assumes the existence in the population of an underlying normally distributed 'liability' (which is due to numerous genetic and environmental factors acting additively, each contributing a small amount of liability) and of a 'threshold' beyond which the individual is affected. For most congenital abnormalities, the nature of these factors remains unknown. Other models assume fewer causal factors although, again, these remain to be identified. The question of how considerable heritable variation for most quantitative/polygenic traits has come to exist is a long-standing one in evolutionary population genetics. Models postulating that its existence is consistent with a balance between recurrent mutation and stabilizing selection or suggesting the possible operation of other mechanisms have been published in the literature. In the absence of knowledge on mechanisms responsible for the stable prevalences of congenital abnormalities or other multifactorial conditions in the population (but which is required to predict the consequences of an increase in mutation rate on their prevalences) it is necessary (a) to adapt and use concepts derived from quantitative and evolutionary population genetics and (b) to examine how sensitive the predictions are to the assumptions used, and how consistent they are with biological realities.

Abnormalities, Radiation-Induced↗
PubMed2006

Quantitative trait loci identified for sugar related traits in a sugarcane (Saccharum spp.) cultivar x Saccharum officinarum population.

The identification of markers linked to quantitative trait loci (QTLs) for increased sugar accumulation could improve the effectiveness of current breeding strategies in sugarcane. Progeny from a cross between a high sucrose producing cultivar, (denotes Australian plant breeding rights), and a Saccharum officinarum clone, IJ76-514 were grown in two field experiments in different years, and evaluated in the early and mid-season phases of crop maturity, to identify robust QTLs in affecting sucrose content in cane. Using an extensive genetic map constructed for with over 1,000 AFLP and SSR markers, a total of 37 QTLs were identified for brix and pol of which, 16 were detected in both experiments. Of these 37 QTL, 30 were clustered into 12 genomic regions in six of the eight homo(eo)logous groups. Each QTL explained from 3 to 9% of the phenotypic variation observed. Both positive and negative effects were identified and the location of the QTLs on linkage groups belonging to the same homo(eo)logy group suggested that a number of the QTLs were allelic forms of the same genes. Of the 37 QTLs identified, the majority were significant in both early and mature cane, but 8 were identified as early specific QTLs and 9 as mature cane QTLs. In total, 97 interactions were significant (P<10(-5)) and these were localised to 32 genomic regions of which 6 were detected with both years' data. Models including all the QTLs explained from 37 to 66% of the total phenotypic variation, depending on the trait. The results will be subsequently applied in marker assisted breeding.

Alleles↗
PubMed1999

Quantitative trait linkage mapping in anthropology.

Recent years have seen rapid progress in several areas of both biomedical and anthropological genetics. While genetic analyses have come to play a significant role in biological anthropology, there has been little use of modern methods for linkage mapping of quantitative trait loci (QTLs). It is now feasible to design research studies to investigate the quantitative genetics of complex phenotypes that are of primary importance to traditional questions in biological anthropology. Complex traits such as functionally significant morphological features, physiological characteristics or aspects of behavior can be examined to estimate the influence of genetic variation on within-species phenotypic variation. In addition, new methods for mapping quantitative trait loci provide opportunities to identify the regions within chromosomes that contain the functional genes of interest. This review summarizes molecular genetic and statistical genetic approaches to QTL mapping, and presents examples of how this approach can expand the scope of anthropological genetics to include mapping and identifying individual genes that influence complex phenotypic traits relevant to fundamental questions in biological anthropology.

Animals↗
PubMed1995

Association and linkage with quantitative traits.

This paper examines two approaches for the analysis of quantitative traits: (1) association studies and (2) linkage studies. The trait studied was Q1 from simulated Problem 2 data set in Genetic Analysis Workshop 9. Our purpose was to evaluate associations present in the data, to identify nongenetic and genetic predictors of the trait, and to explore the simulated genome for linkage. Through the association study, we found evidence for the primary major gene associated with this trait. The linkage study found evidence of residual genetic effect acting through other traits. Adjustments of Q1 for Q2 and Q3 led to a failure to find significant effects of MG2 and MG3. This supports the suggestion that adjustment for genetically influenced traits for effects of other genetic traits can reduce the power to detect major gene effects. In summary, we detected the major gene directly associated with the trait of interest through association studies. Linkage analysis detected evidence for two other genes associated to a lesser degree with the trait.

Analysis of Variance↗
PubMed2002

Mapping quantitative trait loci controlling seed longevity in rice ( Oryza sativa L.).

Quantitative trait loci (QTLs) controlling seed longevity in rice were identified using 98 backcross inbred lines (BILs) derived from a cross between a japonica variety Nipponbare and an indica variety Kasalath. Seeds of each BIL were kept for 12 months at 30 degrees C in dry conditions to promote loss of viability. To measure seed longevity, we performed an additional aging-processing treatment for 2 months at 30 degrees C maintaining seeds at 15% moisture content. We measured the germination percent of these treated seeds at 25 degrees C for 7 days as the degree of seed longevity. The germination of BILs ranged from 0 to 100% with continuous variation. Three putative QTLs for seed longevity, qLG-2, qLG-4 and qLG-9, were detected on chromosome 2, 4 and 9, respectively. Kasalath alleles increased the seed longevity at these QTLs. The QTL with the largest effect, qLG-9, explained 59.5% of total phenotypic variation in BILs. The other two QTLs, qLG-2 and qLG-4, explained 13.4 and 11.6% of the total phenotypic variation, respectively. We also verified the effect of the Kasalath allele of qLG-9 using chromosome segment substitution lines. Furthermore, QTLs for seed dormancy were identified on chromosomes 1, 3, 5, 7 and 11. Based on the comparison of the chromosomal location of QTLs for seed longevity and seed dormancy, these traits seem to be controlled by different genetic factors.

Journal Article↗
PubMed1998

Sib mating designs for mapping quantitative trait loci.

The power to separate the variance of a quantitative trait locus (QTL) from the polygenic variance is determined by the variability of genes identical by descent (IBD) at the QTL. This variability may increase with inbreeding. Selfing, the most extreme form of inbreeding, increases the variability of the IBD value shared by siblings, and thus has a higher efficiency for QTL mapping than random mating. In self-incompatible organisms, sib mating is the closest form of inbreeding. Similar to selfing, sib mating may also increase the power of QTL detection relative to random mating. In this study, we develop an IBD-based method under sib mating designs for QTL mapping. The efficiency of sib mating is then compared with random mating. Monte Carlo simulations show that sib mating designs notably increase the power for QTL detection. When power is intermediate, the power to detect a QTL using full-sib mating is, on average, 7% higher than under random mating. In addition, the IBD-based method proposed in this paper can be used to combine data from multiple families. As a result, the estimated QTL parameters can be applied to a wide statistical inference space relating to the entire reference population.

Animals↗
PubMedDate not supplied

Segregation analysis of quantitative traits.

A review of advanced methods of segregation analysis of quantitative traits on human pedigree data is presented. Special attention was paid to formulation of genetic models tested in the analysis, to the possibility of statistical distinguishing between these models, to the power of the used transmission probability tests, and to the possibility of unambiguous interpretation of the analysis results.

Algorithms↗