Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Trait 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 1,153 records · Page 64Linked to original sources
PubMed2006

[Power estimation for in silico mapping].

A fundamentally new approach to gene mapping of complex traits was suggested recently. It consists in computer analysis of existing databases on the phenotypes and single nucleotide polymorphisms (SNPs) in inbred mouse strains and was termed in silico mapping. The power of this method has been studied by simulating quantitative traits controlled by one, two, or three genes. The results have demonstrated that the power of in silico mapping is high in the case of a monogenic trait. The probability of mapping all genes determining a digenic or, especially, trigenic trait is low. If two or three genes make equal phenotypic contributions to a trait, the proportions of experiments where none of them is localized are 17 and 25%, respectively. In the case of a major gene effect, when the phenotypic contribution of one gene considerably exceeds those of the other genes, the probability to map the major gene is 0.95 and 0.80 for the digenic and trigenic models, respectively. This shows that, in the case of polygenic control, the new method could localize only the genes with major effects, while most genes involved in the control of the trait would not be mapped.

Animals↗
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

Mapping determinants of variation in energy metabolism, respiration and flight in Drosophila.

We employed quantitative trait locus (QTL) mapping to dissect the genetic architecture of a hierarchy of functionally related physiological traits, including metabolic enzyme activity, metabolite storage, metabolic rate, and free-flight performance in recombinant inbred lines of Drosophila melanogaster. We identified QTL underlying variation in glycogen synthase, hexokinase, phosphoglucomutase, and trehalase activity. In each case variation mapped away from the enzyme-encoding loci, indicating that trans-acting regions of the genome are important sources of variation within the metabolic network. Individual QTL associated with variation in metabolic rate and flight performance explained between 9 and 35% of the phenotypic variance. Bayesian QTL analysis identified epistatic effects underlying variation in flight velocity, metabolic rate, glycogen content, and several metabolic enzyme activities. A region on the third chromosome was associated with expression of the glucose-6-phosphate branchpoint enzymes and with metabolic rate and flight performance. These genomic regions are of special interest as they may coordinately regulate components of energy metabolism with effects on whole-organism physiological performance. The complex biochemical network is encoded by an equally complex network of interacting genetic elements with potentially pleiotropic effects. This has important consequences for the evolution of performance traits that depend upon these metabolic networks.

Animals↗
PubMed2006

Sorghum stay-green QTL individually reduce post-flowering drought-induced leaf senescence.

Sorghum is an important source of food, feed, and biofuel, especially in the semi-arid tropics because this cereal is well adapted to harsh, drought-prone environments. Post-flowering drought adaptation in sorghum is associated with the stay-green phenotype. Alleles that contribute to this complex trait have been mapped to four major QTL, Stg1-Stg4, using a population derived from BTx642 and RTx7000. Near-isogenic RTx7000 lines containing BTx642 DNA spanning one or more of the four stay-green QTL were constructed. The size and location of BTx642 DNA regions in each RTx7000 NIL were analysed using 62 DNA markers spanning the four stay-green QTL. RTx7000 NILs were identified that contained BTx642 DNA completely or partially spanning Stg1, Stg2, Stg3, or Stg4. NILs were also identified that contained sub-portions of each QTL and various combinations of the four major stay-green QTL. Physiological analysis of four RTx7000 NILs containing only Stg1, Stg2, Stg3, or Stg4 showed that BTx642 alleles in each of these loci could contribute to the stay-green phenotype. RTx7000 NILs containing BTx642 DNA corresponding to Stg2 retained more green leaf area at maturity under terminal drought conditions than RTx7000 or the other RTx7000 NILs. Under post-anthesis water deficit, a trend for delayed onset of leaf senescence compared with RTx7000 was also exhibited by the Stg2, Stg3, and Stg4 NILs, while significantly lower rates of leaf senescence in relation to RTx7000 were displayed by all of the Stg NILs to varying degrees, but particularly by the Stg2 NIL. Greener leaves at anthesis relative to RTx7000, indicated by higher SPAD values, were exhibited by the Stg1 and Stg4 NILs. The RTx7000 NILs created in this study provide the starting point for in-depth analysis of stay-green physiology, interaction among stay-green QTL and map-based cloning of the genes that underlie this trait.

Chromosome Mapping↗
PubMed2004

Quantitative genetic variation: a post-modern view.

It has become commonplace to map individual quantitative trait loci (QTL) in experimental organisms; the means (line-crosses and dense maps of markers) and motivation (the close relationship between continuous physiological traits and common, complex diseases) are self-evident. Progress in mapping human QTL has been more gradual, an inevitable consequence of genetic mapping in a natural population setting. The common objective of these studies has been to understand the molecular mechanisms underlying individual QTL. Recent theoretical and practical advances shift this focus to a more comprehensive or genomic perspective on quantitative variation. Fisher's infinitesimal model of adaptive evolution, which satisfied quantitative geneticists for over 50 years, has been modified in the light of data from QTL mapping experiments in plants and animals. The resulting exponential model provides a pleasing empirical fit to the distribution of QTL effect sizes, predicts that a large amount of quantitative variation will be explained by a limited number of genes and suggests a new mathematical framework for linkage mapping. Molecular analysis of QTL suggests that coding variants (e.g. allozymes) underlie a fraction of quantitative variation and that variants that affect gene expression (expression QTL, eQTL) have a substantial role. This is supported by genomic experiments that combine expression profiling with classical genetic mapping approaches to reveal a remarkable wealth of quantitative heritable variation in the transcriptome and that cis-and trans-acting regulatory factors are organized in networks reflecting pleiotropy. It is hoped that these advances will enhance our understanding of the genetic basis of complex inherited diseases.

Animals↗
PubMed2005

A model selection-based interval-mapping method for autopolyploids.

While extensive progress has been made in quantitative trait locus (QTL) mapping for diploid species, similar progress in QTL mapping for polyploids has been limited due to the complex genetic architecture of polyploids. To date, QTL mapping in polyploids has focused mainly on tetraploids with dominant and/or codominant markers. Here, we extend this view to include any even ploidy level under a dominant marker system. Our approach first selects the most likely chromosomal marker configurations using a Bayesian selection criterion and then fits an interval-mapping model to each candidate. Profiles of the likelihood-ratio test statistic and the maximum-likelihood estimates (MLEs) of parameters including QTL effects are obtained via the EM algorithm. Putative QTL are then detected using a resampling-based significance threshold, and the corresponding parental configuration is identified to be the underlying parental configuration from which the data are observed. Although presented via pseudo-doubled backcross experiments, this approach can be readily extended to other breeding systems. Our method is applied to single-dose restriction fragment autotetraploid alfalfa data, and the performance is investigated through simulation studies.

Algorithms↗
PubMed1998

Genes on mouse chromosomes 2 and 9 determine variation in ethanol consumption.

Quantitative trait locus (QTL) mapping efforts in alcohol (ethanol) research are beginning to generate promising data that may ultimately lead to the identification of genes influencing alcohol addiction. Rodents have been extensively utilized to study ethanol's rewarding and aversive effects, and to demonstrate the existence of genetic influences on traits such as free-choice ethanol-consumption, ethanol-conditioned place preference and ethanol-conditioned taste aversion. The purpose of the current investigation was to verify or eliminate from further consideration putative QTLs for free-choice ethanol consumption originally identified in BXD Recombinant Inbred (RI) strains and other informative genetic crosses. B6D2F2 mice were utilized in a verification testing strategy to evaluate the viability of putative ethanol consumption QTLs. When data were combined from BXD RI, B6D2F2 and short-term selected line (STSL) mapping studies, verification was obtained for two QTLs, one on Chromosome (Chr) 9 (proximal-mid) and another on Chr 2 (distal), and suggestive verification was obtained for QTLs on Chrs 2 (proximal), 3, 4, 7, and 15. In addition, the possible genetic association of ethanol consumption with conditioned place preference was evaluated. Genetic correlations were estimated from BXD RI strain means, and QTL maps for these traits were compared to evaluate the possibility of a genetic association. The correlational analysis yielded a trend (r = 0.34, p = 0.09), but no statistically significant results. However, comparisons of QTL mapping results between phenotypes suggested some possible genetic overlap for these traits, both putative measures of ethanol reward. These data suggest that the determinants of these two measures are genetically diverse, but may share some common genetic elements.

Alcohol Drinking↗
PubMed1999

Detection of quantitative trait loci affecting caffeine metabolism by interval mapping in a genome-wide scan of C3H/HeJ x APN F(2) mice.

Caffeine metabolite ratios have been widely used to measure cytochrome P-450 1A2 activity in humans. Serum paraxanthine/caffeine ratio is one such index of this activity. We had previously demonstrated genetic variation of this trait among inbred mouse strains. In the present study, we have undertaken a genome-wide scan for quantitative trait loci affecting this trait with an interval mapping approach on an F(2) intercross population of acetaminophen nonsusceptible and C3H/HeJ inbred mice. A statistically significant association (log-likelihood ratio = 25.0) between a locus on chromosome 9, which colocalized with the murine Cyp1a2 locus, and the plasma paraxanthine/caffeine ratio was identified. This result suggested the presence of an expression polymorphism affecting this gene. A second locus was identified on chromosome 1 (log-likelihood ratio = 9.7) for which no obvious candidate gene has been identified. The influence of this locus on the paraxanthine/caffeine index was more significant among males (log-likelihood ratio = 6.3) than females (log-likelihood ratio = 3.6). A third locus was identified on chromosome 4 with a less statistically robust association (log-likelihood ratio = 3.4) to the paraxanthine/caffeine phenotype. Collectively, these three loci accounted for 63.2% of the variation observed in the F(2) population for this phenotype. These results demonstrate the potential for genetic variation arising from factors other than CYP1A2 activity to influence the plasma paraxanthine/caffeine ratio in mice. This study demonstrates the utility of quantitative genetics in the analysis of polygenic drug metabolism.

Animals↗
PubMed1988

Resolution of quantitative traits into Mendelian factors by using a complete linkage map of restriction fragment length polymorphisms.

The conflict between the Mendelian theory of particulate inheritance and the observation of continuous variation for most traits in nature was resolved in the early 1900s by the concept that quantitative traits can result from segregation of multiple genes, modified by environmental effects. Although pioneering experiments showed that linkage could occasionally be detected to such quantitative trait loci (QTLs), accurate and systematic mapping of QTLs has not been possible because the inheritance of an entire genome could not be studied with genetic markers. The use of restriction fragment length polymorphisms (RFLPs) has made such investigations possible, at least in principle. Here, we report the first use of a complete RFLP linkage map to resolve quantitative traits into discrete Mendelian factors, in an interspecific back-cross of tomato. Applying new analytical methods, we mapped at least six QTLs controlling fruit mass, four QTLs for the concentration of soluble solids and five QTLs for fruit pH. This approach is broadly applicable to the genetic dissection of quantitative inheritance of physiological, morphological and behavioural traits in any higher plant or animal.

Chromosome Mapping↗
PubMed2002

QTL mapping and introgression of yield-related traits from Oryza glumaepatula to cultivated rice ( Oryza sativa) using microsatellite markers.

Rice ( Oryza sativa) cultivar development currently faces the task of overcoming yield plateaus, which is difficult due to the narrow genetic base of breeding programs. Oryza glumaepatula is a diploid wild relative of cultivated rice, native to Central and South America, and is therefore a potential source of alleles of agronomic importance to rice breeding programs. We studied 11 agronomic traits in BC(2)F(2) families of the interspecific cross Oryza sativa x O. glumaepatula. Transgressive lines which are almost isogenic to the elite recurrent O. sativa parent were identified for most of these traits. Quantitative trait locus (QTL) analysis was performed by single-point and interval mapping using a molecular map based on 157 microsatellite and STS markers. Marker regions accounting for 14.5 to 72.9% of a phenotypic variation trait were identified in 9 of the 12 rice chromosomes. Positive QTL effects from O. glumaepatula were observed in chromosomal regions associated with tillering and panicle-number traits.

Journal Article↗
PubMed2004

A quantitative trait locus mixture model that avoids spurious LOD score peaks.

In standard interval mapping of quantitative trait loci (QTL), the QTL effect is described by a normal mixture model. At any given location in the genome, the evidence of a putative QTL is measured by the likelihood ratio of the mixture model compared to a single normal distribution (the LOD score). This approach can occasionally produce spurious LOD score peaks in regions of low genotype information (e.g., widely spaced markers), especially if the phenotype distribution deviates markedly from a normal distribution. Such peaks are not indicative of a QTL effect; rather, they are caused by the fact that a mixture of normals always produces a better fit than a single normal distribution. In this study, a mixture model for QTL mapping that avoids the problems of such spurious LOD score peaks is presented.

Genetic Techniques↗
PubMed1998

Haplotype mapping of a major quantitative-trait locus for fetal hemoglobin production, on chromosome 6q23.

Fetal hemoglobin (Hb F) and fetal cell (FC) levels in adults show considerable variation and are influenced by several genetic variants; the major determinants appear to be unlinked to the beta-globin gene cluster. Recently, a trans-acting locus controlling Hb F and FC production has been mapped to chromosome 6q23 in an Asian Indian kindred that includes individuals with heterocellular hereditary persistence of Hb F (HPFH) associated with beta thalassemia. We have extended the kindred by 57 members, bringing the total studied to 210, and have saturated the region with 26 additional markers. Linkage analysis showed tight linkage of the quantitative-trait locus (QTL) to the anonymous markers D6S976 (LOD score 11.3; recombination fraction .00) and D6S270 (LOD score 7.4; recombination fraction .00). Key recombination events now place this QTL within a 1-2-cM interval spanning approximately 1.5 Mb between D6S270 and D6S1626. Furthermore, haplotype analysis has led to a reevaluation of the genealogy and to the identification of additional relationships in the kindred.

Chromosome Mapping↗
PubMed2003

Genetic mapping and QTL analysis of horticultural traits in cucumber ( Cucumis sativus L.) using recombinant inbred lines.

A set of 171 recombinant inbred lines (RIL) were developed from a narrow cross in cucumber ( Cucumis sativus L.; 2n = 2 x = 14) using the determinate ( de), gynoecious ( F), standard-sized leaf line G421 and the indeterminate, monoecious, little-leaf ( ll) line H-19. A 131-point genetic map was constructed using these RILs and 216 F(2) individuals to include 14 SSRs, 24 SCARs, 27 AFLPs, 62 RAPDs, 1 SNP, and three economically important morphological [ F (gynoecy), de (determinate habit), ll (little leaf)] markers. Seven linkage groups spanned 706 cM with a mean marker interval of 5.6 cM. The location of F and de was defined by genetic linkage and quantitative trait locus (QTL) analysis to be associated with SSR loci CSWCT28 and CSWCTT14 at 5.0 cM and 0.8 cM, respectively. RIL-based QTL analysis of the number of lateral branches in three environments revealed four location-independent factors that cumulatively explained 42% of the observed phenotypic variation. QTLs conditioning lateral branching (mlb1.1), fruit length/diameter ratio (ldr1.2) and sex expression (sex1.2) were associated with de. Sex expression was influenced by three genomic regions corresponding to F and de both on linkage Group 1, and a third locus (sex6.1) on linkage Group 6. QTLs conditioning the number of fruit per plant (fpl1.2), the number of lateral branches (mlb1.4) and fruit length/diameter ratio (ldr1.3) were associated with ll. The potential value of these marker-trait associations (i.e., yield components) for plant improvement is portended by the relatively high LOD scores (2.6 to 13.0) and associated R(2) values (1.5% to 32.4%) that are affiliated with comparatively few genetic factors (perhaps 3 to 10).

Chromosome Mapping↗
PubMed2002

Mapping and characterisation of QTL x E interactions for traits determining grain and stover yield in pearl millet.

A mapping population of 104 F(3) lines of pearl millet, derived from a cross between two inbred lines H 77/833-2 x PRLT 2/89-33, was evaluated, as testcrosses on a common tester, for traits determining grain and stover yield in seven different field trials, distributed over 3 years and two seasons. The total genetic variation was partitioned into effects due to season (S), genotype (G), genotype x season interaction (G x S), and genotype x environment-within-season interaction [G x E(S)]. QTLs were determined for traits for their G, G x S, and G x E(S) effects, to assess the magnitude and the nature (cross over/non-crossover) of environmental interaction effects on individual QTLs. QTLs for some traits were associated with G effects only, while others were associated with the effects of both G and G x S and/or G, G x S and G x E(S) effects. The major G x S QTLs detected were for flowering time (on LG 4 and LG 6), and mapped to the same intervals as G x S QTLs for several other traits (including stover yield, harvest index, biomass yield and panicle number m(-2)). All three QTLs detected for grain yield were unaffected by G x S interaction however. All three QTLs for stover yield (mapping on LG 2, LG 4 and LG 6) and one of the three QTLs for grain yield (mapping on LG 4) were also free of QTL x E(S) interactions. The grain yield QTLs that were affected by QTL x E(S) interactions (mapping on LG 2 and LG 6), appeared to be linked to parallel QTL x E(S) interactions of the QTLs for panicle number m(-2) on (LG 2) and of QTLs for both panicle number m(-2) and harvest index (LG 6). In general, QTL x E(S) interactions were more frequently observed for component traits of grain and stover yield, than for grain or stover yield per se.

Chromosome Mapping↗
PubMed2004

Fine mapping of a malting-quality QTL complex near the chromosome 4H S telomere in barley.

Malting quality has long been an active objective in barley (Hordeum vulgare L.) breeding programs.However, it is difficult for breeders to manipulate malting-quality traits because of inheritance complexity and difficulty in evaluation of these quantitative traits. Quantitative trait locus (QTL) mapping provides breeders a promising basis with which to manipulate quantitative trait genes. A malting-quality QTL complex, QTL2, was mapped previously to a 30-cM interval in the short-arm telomere region of barley chromosome 4H in a "Step-toe"/"Morex" doubled haploid population by the North American Barley Genome Project, using an interval mapping method with a relatively low-resolution genetic map. The QTL2 complex has moderate effects on several malting-quality traits, including malt extract percentage(ME), a-amylase activity (AA), diastatic power (DP), malt 13-glucan content (BG), and seed dormancy, which makes it a promising candidate gene source in malting barley-cultivar development. Fine mapping QTL2 is desirable for precisely studying barley malting-quality trait inheritance and for efficiently manipulating QTL2 in breeding. A reciprocal-substitution mapping method was employed to fine map QTL2. Molecular marker-assisted backcrossing was used to facilitate the generation of isolines. Fourteen different types of "Steptoe" isolines, including regenerated "Steptoe" and 13 different types of "Morex" isolines,including regenerated "Morex", were made within a 41.5-cM interval between MWG634 and BCD265B on chromosome 4H. Duplicates were identified for 12 "Steptoe" and 12 "Morex" isoline types. The isolines together with "Steptoe" and "Morex" were grown variously at three locations in 2 years for a total of five field environments.Four malting-quality traits were measured: ME, DP, AA,and BG. Few significant differences were found between duplicate isolines for these traits. A total of 15 putative QTLs were mapped; three for ME, four for DP, six for AA,and two for BG. Background genotype seemed to make a difference in expression/detection of QTLs. Of the 15 QTLs identified, ten were from the "Morex" and only five from the "Steptoe" background. By combining the results from different years, field environments, and genetic backgrounds and taking into account overlapping QTLsegments, six QTLs can be conservatively estimated: two each for ME and AA and one each for DP and BG with chromosome segments ranging from 0.7 cM to 27.9 cM. A segment of 15.8 cM from the telomere (MWG634-CDO669) includes all or a portion of all QTLs identified. Further study and marker-assisted breeding should focus on this 15.8-cM chromosome region.

Breeding↗
PubMed2003

Study of candidate genes for glycolytic potential of porcine skeletal muscle: identification and analysis of mutations, linkage and physical mapping and association with meat quality traits in pigs.

Several genes (PRKAA2, PRKAB1, PRKAB2, PRKAG3, GAA, GYS1, PYGM, ALDOA, GPI, LDHA, PGAM2 and PKM2), chosen according to their role in the regulation of the energy balance and in the glycogen metabolism and glycolysis of the skeletal muscle, were studied. Eleven single nucleotide polymorphisms (SNPs) were identified in six of these genes (PRKAB1, GAA, PYGM, LDHA, PGAM2 and PKM2). Allele frequencies were analyzed in seven different pig breeds for these loci and for a polymorphism already described for GPI and for three polymorphic sites already reported at the PRKAG3 locus (T30N, G52S and I199V). Linkage mapping assigned PYGM and LDHA to porcine chromosome (SSC) 2, PKM2 to SSC7, GAA to SSC12, PRKAB1 to SSC14 and PGAM2 to SSC18. Physical mapping, obtained by somatic cell hybrid panel analysis, confirmed the linkage assignments of PRKAB1 and GAA and localized ALDOA, PRKAB2 and GYS1 to SSC3, SSC4 and SSC6, respectively. Pigs selected for the association study, for which several meat quality traits were measured, were first genotyped at the PRKAG3 R200Q polymorphic site (RN locus), in order to exclude carriers of the 200Q allele, and then were genotyped for all the mutations considered in this work. Significant associations (P < or = 0.001) were observed for the PRKAG3 T30N and G52S polymorphic sites with meat colour (L* at 24 h post mortem). PGAM2 and PKM2 were significantly associated (P = 0.01) with drip loss percentage and glycogen content at one hour post mortem, respectively.

Animals↗
PubMed1999

High resolution mapping and identification of new quantitative trait loci (QTL) affecting susceptibility to Marek's disease.

Marek's disease (MD) is a lymphoproliferative disease of chickens that costs the poultry industry approximately $1 billion annually. Genetic resistance to MD is gaining increased attention to augment vaccinal control as disease outbreaks occur more frequently. Previously, analysis of a 272 F2 White Leghorn resource population measured for many MD traits and genotyped for 78 microsatellite markers revealed two and four quantitative trait loci (QTL) with significant and suggestive association, respectively, to one or more MD associated traits. Additional genetic markers have since been scored on the MD resource population to increase QTL resolution and genome coverage. Saturation of four of the QTL regions with 17 markers revealed five new QTL while 32 markers extended the genome coverage by 400 + CM and uncovered three more QTL. QTL analysis by single-point and interval mapping algorithms agreed well when marker saturation was approximately 20 CM or less. Currently 127 genetic markers cover approximately 68% of the genome that contain up to 14 MD QTL associated to one or more MD trait; seven at the significant level and seven at the suggestive level. Individually each QTL accounts for 2-10% of the variation and, in general, resistance was dominant although the resistant allele may come from either parental line. This study suggests that a limited number of genomic regions play a major role in the genetic control of MD resistance. Markers linked to these loci may be useful for selection of MD resistant stock by the poultry industry following verification of the association within their breeding populations.

Animals↗
PubMed2001

In silico mapping of complex disease-related traits in mice.

Experimental murine genetic models of complex human disease show great potential for understanding human disease pathogenesis. To reduce the time required for analysis of such models from many months down to milliseconds, a computational method for predicting chromosomal regions regulating phenotypic traits and a murine database of single nucleotide polymorphisms were developed. After entry of phenotypic information obtained from inbred mouse strains, the phenotypic and genotypic information is analyzed in silico to predict the chromosomal regions regulating the phenotypic trait.

Algorithms↗