Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “QTL mapping”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

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

At least 1,099 records · Page 61Linked to original sources
PubMed2006

High resolution mapping of chromosomal regions controlling resistance to gastrointestinal nematode infections in an advanced intercross line of mice.

Fine mapping of quantitative trait loci (QTL) associated with resistance to the gastrointestinal parasite Heligmosomoides polygyrus was achieved on F(6)/F(7) offspring (1076 mice) from resistant (SWR) and susceptible (CBA) mouse strains by selective genotyping (top and bottom 20% selected on total worm count in week 6). Fecal egg counts were recorded at weeks 2, 4, and 6, and the average was also analyzed. Blood packed cell volume in weeks 3 and 6 and five immunological traits (mucosal mast cell protease 1, granuloma score, IgG1 against adult worm, IgG1, and IgE to L4 antigen) were also recorded. On Chromosome 1 single-trait analyses identified a QTL with effects on eight traits located at about 24 cM on the F(2) mouse genome database (MGD) linkage map, with a 95% confidence interval (CI) of 20-32 cM established from a multitrait analysis. On Chromosome 17 a QTL with effects on nine traits was located at about 18 cM on the MGD map (CI 17.9-18.4 cM). Strong candidate genes for the QTL position on Chromosome 1 include genes known to be involved in regulating immune responses and on Chromosome 17 genes within the MHC, notably the Class II molecules and tumor necrosis factor.

Animals↗
PubMed2003

Further dissection of a genomic locus associated with behavioral activity in the Wistar-Kyoto hyperactive rat, an animal model of hyperkinesis.

Molecular genetic studies of attention-deficit hyperactivity disorder (ADHD) are a major focus of current research since this syndrome has been shown to be highly heritable.(1) Our approach has been to search for quantitative trait loci (QTL) in a genetic animal model of hyperkinesis, the Wistar-Kyoto hyperactive (WKHA) rat, by a whole-genome scan analysis. In a previous article, we reported the detection of a major QTL associated with behavioral activity in an F2 cross between WKHA and Wistar-Kyoto (WKY) rat strains.(2) Here, we extend our analysis of this cross by adding new genetic markers, now defining a 10 cM interval on rat chromosome 8 associated with ambulatory and exploratory activities. Then we present a replication of this QTL detection, at least for exploratory activity, by a new genetic mapping analysis of an activity QTL in an F2 cross between the WKHA and Brown Norway (BN) rat strains. Overall, the results provide compelling evidence for the presence of gene(s) influencing activity at this locus. The QTL interval has been refined such that the human orthologous region could be defined and tested in human populations for association with ADHD. Ultimately, the improved dissection of this genomic locus should allow the identification of the causal genes.

Animals↗
PubMed2006

Positional relationships between photoperiod response QTL and photoreceptor and vernalization genes in barley.

Winterhardiness has three primary components: photoperiod (day length) sensitivity, vernalization response, and low temperature tolerance. Photoperiod and vernalization regulate the vegetative to reproductive phase transition, and photoperiod regulates expression of key vernalization genes. Using two barley mapping populations, we mapped six individual photoperiod response QTL and determined their positional relationship to the phytochrome and cryptochrome photoreceptor gene families and the vernalization regulatory genes HvBM5A, ZCCT-H, and HvVRT-2. Of the six photoreceptors mapped in the current study (HvPhyA and HvPhyB to 4HS, HvPhyC to 5HL, HvCry1a and HvCry2 to 6HS, and HvCry1b to 2HL), only HvPhyC coincided with a photoperiod response QTL. We recently mapped the candidate genes for the 5HL VRN-H1 (HvBM5A) and 4HL VRN-H2 (ZCCT-H) loci, and in this study, we mapped HvVRT-2, the barley TaVRT-2 ortholog (a wheat flowering repressor regulated by vernalization and photoperiod) to 7HS. Each of these three vernalization genes is located in chromosome regions determining small photoperiod response QTL effects. HvBM5A and HvPhyC are closely linked on 5HL and therefore are currently both positional candidates for the same photoperiod effect. The coincidence of photoperiod-responsive vernalization genes with photoperiod QTL suggests vernalization genes should also be considered candidates for photoperiod effects.

Alleles↗
PubMed2005

Genetic characterization of QTL associated with resistance to Fusarium head blight in a doubled-haploid spring wheat population.

Fusarium head blight (FHB) is one of the most important fungal wheat diseases worldwide. Understanding the genetics of FHB resistance is the key to facilitating the introgression of different FHB resistance genes into adapted wheat. The objectives of the present study were to detect and map quantitative trait loci (QTL) associated with FHB resistance genes and characterize the genetic components of the QTL in a doubled-haploid (DH) spring wheat population using both single-locus and two-locus analysis. A mapping population, consisting of 174 DH lines from the cross between DH181 (resistant) and AC Foremost (susceptible), was evaluated for type I resistance to initial infection during a 2-year period in spray-inoculated field trials, for Type II resistance to fungal spread within the spike in 3 greenhouse experiments using single-floret inoculation, and for resistance to kernel infection in a 2001 field trial. One-locus QTL analysis revealed 7 QTL for type I resistance on chromosome arms 2DS, 3AS, 3BS, 3BC (centromeric), 4DL, 5AS, and 6BS, 4 QTL for type II resistance on chromosomes 2DS, 3BS, 6BS, and 7BL, and 6 QTL for resistance to kernel infection on chromosomes 1DL, 2DS, 3BS, 3BC, 4DL, and 6BS. Two-locus QTL analysis detected 8 QTL with main effects and 4 additive by additive epistatic interactions for FHB resistance and identified novel FHB resistance genes for the first time on chromosomes 1DL, 4AL, and 4DL. Neither significant QTL by environment interactions nor epistatic QTL by environment interactions were found for either type I or type II resistance. The additive effects of QTL explained most of the phenotypic variance for FHB resistance. Marker-assisted selection for the favored alleles at multiple genomic regions appears to be a promising tool to accelerate the introgression and pyramiding of different FHB resistance genes into adapted wheat genetic backgrounds.

Chromosome Mapping↗
PubMed2004

Mapping quantitative trait loci with censored observations.

The existing statistical methods for mapping quantitative trait loci (QTL) assume that the phenotype follows a normal distribution and is fully observed. These assumptions may not be satisfied when the phenotype pertains to the survival time or failure time, which has a skewed distribution and is usually subject to censoring due to random loss of follow-up or limited duration of the experiment. In this article, we propose an interval-mapping approach for censored failure time phenotypes. We formulate the effects of QTL on the failure time through parametric proportional hazards models and develop efficient likelihood-based inference procedures. In addition, we show how to assess genome-wide statistical significance. The performance of the proposed methods is evaluated through extensive simulation studies. An application to a mouse cross is provided.

Chromosome Mapping↗
PubMed2002

A statistical model for the genetic origin of allometric scaling laws in biology.

Many biological processes, from cellular metabolism to population dynamics, are characterized by particular allometric scaling (power-law) relationships between size and rate. Although such allometric relationships may be under genetic determination, their precise genetic mechanisms have not been clearly understood due to a lack of a statistical analytical method. In this paper, we present a basic statistical framework for mapping quantitative genes (or quantitative trait loci, QTL) responsible for universal quarter-power scaling laws of organic structure and function with the entire body size. Our model framework allows the testing of whether a single QTL affects the allometric relationship of two traits or whether more than one linked QTL is segregating. Like traditional multi-trait mapping, this new model can increase the power to detect the underlying QTL and the precision of its localization on the genome. Beyond the traditional method, this model is integrated with pervasive scaling laws to take advantage of the mechanistic relationships of biological structures and processes. Simulation studies indicate that the estimation precision of the QTL position and effect can be improved when the scaling relationship of the two traits is considered. The application of our model in a real example from forest trees leads to successful detection of a QTL governing the allometric relationship of third-year stem height with third-year stem biomass. The model proposed here has implications for genetic, evolutionary, biomedicinal and breeding research.

Animals↗
PubMed2006

High-resolution mapping of quantitative trait loci affecting increased life span in Drosophila melanogaster.

Limited life span and senescence are near-universal characteristics of eukaryotic organisms, controlled by many interacting quantitative trait loci (QTL) with individually small effects, whose expression is sensitive to the environment. Analyses of mutations in model organisms have shown that genes affecting stress resistance and metabolism affect life span across diverse taxa. However, there is considerable segregating variation for life span in nature, and relatively little is known about the genetic basis of this variation. Replicated lines of Drosophila that have evolved increased longevity as a correlated response to selection for postponed senescence are valuable resources for identifying QTL affecting naturally occurring variation in life span. Here, we used deficiency complementation mapping to identify at least 11 QTL on chromosome 3 that affect variation in life span between five old (O) lines selected for postponed senescence and their five base (B) population control lines. Most QTL were sex specific, and all but one affected multiple O lines. The latter observation is consistent with alleles at intermediate frequency in the base population contributing to the response to selection for postponed senescence. The QTL were mapped with high resolution and contained from 12 to 170 positional candidate genes.

Animals↗
PubMed2004

A single major chromosomal region controls natural killer cell-like activity in rainbow trout.

We report the identification of a single major chromosomal region controlling natural killer (NK) cell-like activity in rainbow trout (Oncorhynchus mykiss). A genetic map based on 484 AFLP and 39 microsatellite genotypes from 106 doubled haploid fish was constructed. These fish were produced by androgenesis from a hybrid of two clonal lines divergent in NK-like activity. NK-like activities for 75 of the doubled haploids were quantified by an in vitro chromium release assay utilizing (51)Cr-labeled YAC-1 target cells. Composite interval mapping revealed a single major quantitative trait locus (QTL) associated with NK-like activity in this rainbow trout model. Genetic mapping revealed this QTL to also be unlinked to: fragmented MHC class I and MHC class II regions, the leukocyte receptor cluster, the natural killer cell enhancement factor ( NKEF) gene, the RAG-1 gene, and two QTL associated with resistance to infectious pancreatic necrosis virus in rainbow trout. Collectively, these results extend the utility of rainbow trout as an immunological model and are consistent with the idea that a single chromosomal region homologous to the natural killer cell complex (NKC) located on syntenic portions of mouse chromosome (Chr) 6, human Chr 12, and rat Chr 4 may exist in a lower vertebrate model.

Animals↗
PubMed2006

A quantitative trait locus for oleic fatty acid content on Sus scrofa chromosome 7.

A partial genome scan using microsatellite markers was conducted to detect quantitative trait loci (QTLs) for 10 fatty acid contents of backfat on 15 chromosomes in a porcine resource population. Two QTLs were discovered on Sus scrofa chromosome 4 (SSC4) and SSC7. The QTL on SSC4 was located between marker loci sw1336 and sw512, and this QTL was detected (P < 0.05) only for linoleic acid. Its position was in proximity of those mapped for linoleic acid content in previous studies. The QTL on SSC7 was mapped between markers swr1343 and sw2155, and it was significant (P < 0.05) only for oleic acid. A novelty of the QTL for oleic acid was suggested because the QTL was located far from any other QTLs previously mapped for fatness traits. The QTL on SSC7 explained 19% of phenotypic variation for oleic acid content. Further studies on fine mapping and positional comparative candidate gene analysis would be the next step toward better understanding of the genetic architecture of fatty acid contents.

Animals↗
PubMed2004

Quantitative trait loci affecting knockdown resistance to high temperature in Drosophila melanogaster.

Knockdown resistance to high temperature is an ecologically important trait in small insects. A composite interval mapping was performed on the two major autosomes of Drosophila melanogaster to search for quantitative trait loci (QTL) affecting knockdown resistance to high temperature (KRHT). Two dramatically divergent lines from geographically different thermal environments were artificially selected on KRHT. These lines were crossed to produce two backcross (BC) populations. Each BC was analysed for 200 males with 18 marker loci on chromosomes 2 and 3. Three X-linked markers were used to test for X-linked QTL in an exploratory way. The largest estimate of autosome additive effects was found in the pericentromeric region of chromosome 2, accounting for 19.26% (BC to the low line) and 29.15% (BC to the high line) of the phenotypic variance in BC populations, but it could represent multiple closely linked QTL. Complete dominance was apparent for three QTL on chromosome 3, where heat-shock genes are concentrated. Exploratory analysis of chromosome X indicated a substantial contribution of this chromosome to KRHT. The results show that a large-effect QTL with dominant gene action maps on the right arm of chromosome 3. Further, the results confirm that QTL for heat resistance are not limited to chromosome 3.

Animals↗
PubMed1996

Detection of obesity QTLs on mouse chromosomes 1 and 7 by selective DNA pooling.

The inheritance of obesity has been analyzed in an intercross between the lean 129/Sv mouse strain and the obesity-prone EL/Suz mouse strain. The weights of three major fat pads were determined on 4-month-old mice, and the sum of these weights, divided by body weight, was used as an adiposity index. The strategy of selective DNA pooling was used as a primary screen to identify putative quantitative trait loci (QTLs) affecting adiposity index. DNA pools representing the leanest 15% and fattest 15% of the F2 progeny were compared for differential allelic enrichment using widely dispersed microsatellite variants. To evaluate putative QTLs, individual genotyping and interval mapping were employed to estimate QTL effects and assess statistical significance. One QTL affecting adiposity index, which accounted for 12.3% of phenotypic variance in gender-merged data, was mapped to the central region of Chromosome (Chr) 7. The QTL allele inherited from EL conferred increased adiposity. A second QTL that accounts for 6.3% of phenotypic variance was identified on Chr 1 near D1Mit211. At both QTLs, the data are consistent with dominant inheritance of the allele contributing to obesity. The possible relationships between these QTLs and previously described obesity QTLs, major obesity mutations, and candidate genes are discussed.

Adipose Tissue↗
PubMed2006

Mixture cure model with an application to interval mapping of quantitative trait loci.

When censored time-to-event data are used to map quantitative trait loci (QTL), the existence of nonsusceptible subjects entails extra challenges. If the heterogeneous susceptibility is ignored or inappropriately handled, we may either fail to detect the responsible genetic factors or find spuriously significant locations. In this article, an interval mapping method based on parametric mixture cure models is proposed, which takes into consideration of nonsusceptible subjects. The proposed model can be used to detect the QTL that are responsible for differential susceptibility and/or time-to-event trait distribution. In particular, we propose a likelihood-based testing procedure with genome-wide significance levels calculated using a resampling method. The performance of the proposed method and the importance of considering the heterogeneous susceptibility are demonstrated by simulation studies and an application to survival data from an experiment on mice infected with Listeria monocytogenes.

Algorithms↗
PubMed2003

QTL and epistatic interaction underlying leaf chlorophyll and H2O2 content variation in rice (Oryza sativa L.).

It is meaningful to study the genetics of the traits associated with photosynthesis such as leaf chlorophyll and H2O2 contents for high yield breeding in rice. A mapping population of 98 BC1F9 lines (backcross Inbred Lines, BIL), derived from a backcross of Nipponbare (japonica)/Kasalath(indica)//Nipponbare by the single-seed-descent methods, was employed to map quantitative trait loci (QTL) underlying such rice traits as leaf chlorophyll and H2O2 contents. Five and two QTLs were detected for leaf Chlorophyll and H2O2 content variation, respectively. Among the QTLs detected, q-Chl1 on chromosome 1 accounted for 22% variation for leaf chlorophyll content variation. The alleles from Nipponbare increased stature at the locus; On the other hand, q-H2O2(1) which associated with H2O2 content was also located on the same region as q-Chl1. The alleles from Nipponbare decreased stature at this locus. The 2 traits have the 2 QTL sharing the same chromosome locations, which was located between C86 and C813 on chromosome 1. Epistasis analysis showed QTL with interaction distributed on chromosome 2, 6, 11 and 12. However, no QTL interacted with q-Chl1 or q-H2O2(1) was detected. It can be deduced that alleles from Nipponbare at the region between C86 and C813 on chromosome 1 increases leaf chlorophyll content and decreases H2O2 content at the mean time with significant additive effect but little epistasis.

Chlorophyll↗
PubMed1997

Mapping the chicken genome.

Most economically important traits are genetically complex and controlled by numerous genes. A quality genetic map is a prerequisite for identifying quantitative trait loci (QTL) that contain the genes involved in these traits. Currently, there are two internationally recognized reference families that are used to build genetic maps. In this paper, the East Lansing (EL) genetic map is described in detail. Presently, the EL genetic map contains 617 genetic markers, of which 589 are resolved into 41 linkage groups. The map coverage within linkage groups is over 2,700 cM, which is about the estimated size of the chicken genome. There are 322 microsatellite markers, which greatly enhances the utility of this genetic map for genome-wide QTL searches. Also, 101 genes have been mapped, which will aid in the development of a comparative map. Further efforts to improve the genetic map and the potential for the map to identify QTL are discussed.

Animals↗
PubMedDate not supplied

Cytogenetic mapping of 25 goat mammary gland Expressed Sequence Tags (ESTs).

Today, there is a shift towards a positional candidate approach in the molecular identification of genes. This study reports on an Expressed Sequence Tags (ESTs) mapping initiative in goats, based on sequence information gathered from a previous mammary gland cDNA systematic sequencing project. A total of 25 novel genes was localised cytogenetically on 16 goat chromosomes. Six of these ESTs were found to map to cattle milk QTL regions. These results made it possible to assess the use of ESTs as a shortcut to the molecular identification of some QTLs and as a valuable tool for comparative mapping.

Journal Article↗
PubMed2002

On the efficiency of composite interval mapping in an outbred population.

Composite interval mapping (CIM) has been successfully applied to the detection of QTL in experimental animals and plants. However, practical analyses based on CIM have been reported mainly for populations derived from cross between inbred lines. There are few studies on QTL analyses with CIM in outbred populations. To evaluate the applicability of CIM to outbred populations is prerequisite for the fine mapping of QTL in industrial animals such as pig and chicken. Some markers are usually not fully informative in outbred populations. In application of CIM to outbred populations, the influence of inclusion of such uninformative markers used as covariates on the efficiency of CIM should be investigated. In this paper a least-squares method for CIM was formalized in an F(2) population derived by crossing two outbred lines. The efficiencies of CIM were evaluated for outbred populations in comparison with simple interval mapping (SIM) for several cases of marker informativeness using simulations. By incorporating markers linked to a tested position as well as those unlinked, CIM showed a higher efficiency to separate two linked QTL over SIM. The efficiency of dissection was enhanced as the marker informativeness was increased. The power of CIM to detect an isolated QTL was improved by excluding markers linked to a tested position from covariates and higher than SIM regardless of marker informativeness. In conclusion, CIM is a useful procedure for the analysis of QTL in outbred populations even under low marker informativeness.

Animals↗
PubMed1997

Association of the brain natriuretic peptide gene with blood pressure and heart weight in the rat.

1. Atrial natriuretic peptide (ANP) and brain natriuretic peptide (BNP) are important in the control of body fluid homeostasis, blood pressure (BP) regulation and vascular remodelling. The genes for these peptides may, therefore, be involved in the pathogenesis of genetic hypertension. We have previously described a quantitative trait locus (QTL) for BP in the ANP gene region on rat chromosome 5. We have now assessed the possibility that this QTL lies at the closely linked BNP locus. 2. Intra-arterial BP and heart weight were measured in 12-week-old (n = 207) and 24-week-old (n = 88) F2 rats derived from crosses between Wistar-Kyoto normotensive rats and spontaneously hypertensive rats. We designed polymerase chain reaction primers to amplify a microsatellite in the BNP gene from genomic DNA. Analysis of variance was used for cosegregation analysis. Linkage mapping and localization of QTL was performed using the Mapmaker computer package. 3. A significant correlation was found between genotype for the BNP gene and systolic BP (P < 0.001) in 12-week-old rats. The ANP gene, but not the BNP gene, was associated with systolic BP in 24 week rats. There was no segregation of heart weight with BNP genotype at 12 or 24 weeks of age. The BNP gene mapped approximately 20 cM from the ANP gene in our rat hybrids, away from the previously described QTL. There was evidence for a second BP locus near to but distinct from the BNP gene. 4. These results suggest that BP QTL are present in the natriuretic peptide gene region but that the ANP and BNP genes themselves have no major effect on BP in this cross.

Animals↗
PubMed1994

Constructing confidence intervals for QTL location.

We describe a method for constructing the confidence interval of the QTL location parameter. This method is developed in the local asymptotic framework, leading to a linear model at each position of the putative QTL. The idea is to construct a likelihood ratio test, using statistics whose asymptotic distribution does not depend on the nuisance parameters and in particular on the effect of the QTL. We show theoretical properties of the confidence interval built with this test, and compare it with the classical confidence interval using simulations. We show in particular, that our confidence interval has the correct probability of containing the true map location of the QTL, for almost all QTLs, whereas the classical confidence interval can be very biased for QTLs having small effect.

Chromosome Mapping↗