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At least 487 records · Page 27Linked to original sources
PubMed2004

Using genetic admixture to study the biology of obesity traits and to map genes in admixed populations.

Differences among ethnic and racial groups in obesity-related traits have been clearly established in the scientific literature. To explore the genetic component underlying these differences, the genetic admixture approach has been used. In this approach, ancestry informative genetic markers are used to estimate a quantitative value representing the degree of ancestral background in individuals of admixed genetic background. Genetic admixture has been successfully used to explain racial and ethnic variation in obesity related traits; however, the understanding and measure of cultural and environmental components that also influence these phenotypes still requires further exploration.

American Indian or Alaska Native↗
PubMed2005

Assessing the power of tag SNPs in the mapping of quantitative trait loci (QTL) with extremal and random samples.

BACKGROUND: Recent studies have indicated that the human genome could be divided into regions with low haplotype diversity interspersed with regions of high haplotype diversity. In regions of low haplotype diversity, a small fraction of SNPs (tag SNPs) are sufficient to account for most of the haplotype diversity of the human genome. These tag SNPs can be extremely useful for testing the association of a marker locus with a qualitative or quantitative trait locus in that it may not be necessary to genotype all the SNPs. When tag SNPs are used to reduce the genotyping effort in association studies, it is important to know how much power is lost. It is also important to know how much power is gained when tag SNPs instead of the same number of randomly chosen SNPs are used. RESULTS: We design a simulation study to tackle these problems for a variety of quantitative association tests using either case-parent samples or unrelated population samples. First, the samples are generated based on the quantitative trait model with the assumption of either an extremal sampling scheme or a random sampling scheme. Second, a small number of samples are selected to determine the haplotype blocks and the tag SNPs. Third, the statistical power of the tests is evaluated using four kinds of data: (1) all the SNPs and the corresponding haplotypes, (2) the tag SNPs and the corresponding haplotypes, (3) the same number of evenly spaced SNPs with minor allele frequency greater than a threshold and the corresponding haplotypes, (4) the same number of randomly chosen SNPs and their corresponding haplotypes. CONCLUSION: Our results suggest that in most situations genotyping efforts can be significantly reduced by using tag SNPs for mapping the QTL in association studies without much loss of power, which is consistent with previous studies on association mapping of qualitative traits. For all situations considered, two-locus haplotype analysis using tag SNPs are more powerful than those using the same number of randomly selected SNPs, but the degree of such power differences depends upon the sampling scheme and the population history.

Chromosome Mapping↗
PubMed2003

Mapping quantitative physiological traits in apple (Malus x domestica Borkh.).

Efficient breeding and selection of high-quality apple cultivars requires knowledge and understanding of the underlying genetics. The availability of genetic linkage maps constructed with molecular markers enables the detection and analysis of major genes and quantitative trait loci contributing to the quality traits of a genotype. A segregating population of the cross between the apple varieties 'Fiesta' (syn. 'Red Pippin') and 'Discovery' has been observed over three years at three different sites in Switzerland and data on growth habit, blooming behaviour, juvenile period and fruit quality has been recorded. QTL analyses were performed, based on a genetic linkage map consisting of 804 molecular markers and covering all 17 apple chromosomes. With the maximum likelihood based interval mapping method, the investigated complex traits could be dissected into a number of QTLs affecting the observed characters. Genomic regions participating in the genetic control of stem diameter, plant height increment, leaf size, blooming time, blooming intensity, juvenile phase length, time of fruit maturity, number of fruit, fruit size and weight, fruit flesh firmness, sugar content and fruit acidity were identified and compared with previously mapped QTLs in apple. Although 'Discovery' fruit displayed a higher acid content, both acidity QTLs were attributed to the sweeter parent 'Fiesta'. This indicated homozygosity at the acidity loci in 'Discovery' preventing their detection in the progeny due to the lack of segregation.

Chromosome Mapping↗
PubMed2004

Coalescent-based association mapping and fine mapping of complex trait loci.

We outline a general coalescent framework for using genotype data in linkage disequilibrium-based mapping studies. Our approach unifies two main goals of gene mapping that have generally been treated separately in the past: detecting association (i.e., significance testing) and estimating the location of the causative variation. To tackle the problem, we separate the inference into two stages. First, we use Markov chain Monte Carlo to sample from the posterior distribution of coalescent genealogies of all the sampled chromosomes without regard to phenotype. Then, averaging across genealogies, we estimate the likelihood of the phenotype data under various models for mutation and penetrance at an unobserved disease locus. The essential signal that these models look for is that in the presence of disease susceptibility variants in a region, there is nonrandom clustering of the chromosomes on the tree according to phenotype. The extent of nonrandom clustering is captured by the likelihood and can be used to construct significance tests or Bayesian posterior distributions for location. A novelty of our framework is that it can naturally accommodate quantitative data. We describe applications of the method to simulated data and to data from a Mendelian locus (CFTR, responsible for cystic fibrosis) and from a proposed complex trait locus (calpain-10, implicated in type 2 diabetes).

Alleles↗
PubMed2004

Mapping of quantitative trait loci for partial resistance to Mycosphaerella pinodes in pea (Pisum sativum L.), at the seedling and adult plant stages.

The inheritance of resistance to Ascochyta blight, an economically important foliar disease of field pea ( Pisum sativum L.) worldwide, was investigated. Breeding resistant pea varieties to this disease, caused by Mycosphaerella pinodes, is difficult due to the availability of only partial resistance. We mapped and characterized quantitative trait loci (QTLs) for resistance to M. pinodes in pea. A population of 135 recombinant inbred lines (RILs), derived from the cross between DP (partially resistant) and JI296 (susceptible), was genotyped with morphological, RAPD, SSR and STS markers. A genetic map was elaborated, comprising 206 markers distributed over eight linkage groups and covering 1,061 cM. The RILs were assessed under growth chamber and field conditions at the seedling and adult plant stages, respectively. Six QTLs were detected at the seedling stage, which together explained up to 74% of the variance. Ten QTLs were identified at the adult plant stage in the field, and together these explained 56.6-67.1% of the variance, depending on the resistance criteria and the organ considered. Four QTLs were detected under both growth chamber and field conditions, suggesting they were not plant-stage dependent. Three QTLs for flowering date and three QTLs for plant height were also identified in the RIL population, some of which co-located with QTLs for resistance. The relationship between QTLs for resistance to M. pinodes, plant height and flowering date is discussed.

Analysis of Variance↗
PubMedDate not supplied

Linkage disequilibrium fine mapping of quantitative trait loci: a simulation study.

Recently, the use of linkage disequilibrium (LD) to locate genes which affect quantitative traits (QTL) has received an increasing interest, but the plausibility of fine mapping using linkage disequilibrium techniques for QTL has not been well studied. The main objectives of this work were to (1) measure the extent and pattern of LD between a putative QTL and nearby markers in finite populations and (2) investigate the usefulness of LD in fine mapping QTL in simulated populations using a dense map of multiallelic or biallelic marker loci. The test of association between a marker and QTL and the power of the test were calculated based on single-marker regression analysis. The results show the presence of substantial linkage disequilibrium with closely linked marker loci after 100 to 200 generations of random mating. Although the power to test the association with a frequent QTL of large effect was satisfactory, the power was low for the QTL with a small effect and/or low frequency. More powerful, multi-locus methods may be required to map low frequent QTL with small genetic effects, as well as combining both linkage and linkage disequilibrium information. The results also showed that multiallelic markers are more useful than biallelic markers to detect linkage disequilibrium and association at an equal distance.

Animals↗
PubMed2002

Mapping of quantitative trait loci for field resistance to Fusarium head blight in an European winter wheat.

Fusarium head blight (FHB) caused by Fusarium culmorum is an economically important disease of wheat that may cause serious yield and quality losses under favorable climate conditions. The development of disease-resistant cultivars is the most effective control strategy. Worldwide, there is heavy reliance on the resistance pool originating from Asian wheats, but excellent field resistance has also been observed among European winter wheats. The objective of this study was to map and characterize quantitative traits loci (QTL) of resistance to FHB among European winter wheats. A population of 194 recombinant inbred lines (RILs) was genotyped from a cross between two winter wheats Renan (resistant)/Récital (susceptible) with microsatellites, AFLP and RFLP markers. RILs were assessed under field conditions For 3 years in one location. Nine QTLs were detected, and together they explained 30-45% of the variance, depending on the year. Three of the QTLs were stable over the 3 years. One stable QTL, QFhs.inra.2b, was mapped to chromosome 2B and two QTLs QFhs.inra.5a2 and QFhs.inra5a3, to chromosome 5A; each of these QTLs explained 6.9-18.6% of the variance. Other QTLs were identified on chromosome 2A, 3A, 3B, 5D, and 6D, but these had a smaller effect on FHB resistance. One of the two QTLs on chromosome 5A was linked to gene B1 controlling the presence of awns. Overlapping QTLs for FHB resistance were those for plant height or/and flowering time. Our results confirm that wheat chromosomes 2A, 3A, 3B, and 5A carry FHB resistance genes, and new resistance factors were identified on chromosome arms 2BS and 5AL. Markers flanking these QTLs should be useful tools for combining the resistance to FHB of Asian and European wheats to increase the resistance level of cultivars.

Biometry↗
PubMed1998

Least squares interval mapping of quantitative trait loci under the infinitesimal genetic model in outbred populations.

Genetic marker and phenotypic data for a quantitative trait were simulated on 20 paternal half-sib families with 100 progeny to investigate properties of within-family-regression interval mapping of a postulated single quantitative trait locus (QTL) in a marker interval under the infinitesimal genetic model, which has been the basis of the application of quantitative genetics to genetic improvement programs, and to investigate use of the infinitesimal model as null hypothesis in testing for presence of a major QTL. Genetic effects on the marked chromosome were generated based on a major gene model, which simulated a central biallelic QTL, or based on 101 biallelic QTL of equal effect, which approximated the infinitesimal model. The marked chromosome contained 0, 3.3%, 13.3%, or 33.3% of genetic variance and heritability was 0.25 or 0.70. Under the polygenic model with 3.3% of genetic variance on the marked chromosome, which corresponds to the infinitesimal model for the bovine, significant QTL effects were found for individual families. Correlations between estimates of QTL effects and true chromosome substitution effects were 0.29 and 0.47 for heritabilities of 0.25 and 0.70 but up to 0.85 with 33.3% of polygenic variance on the marked chromosome. These results illustrate the potential of marker-assisted selection even under the infinitesimal genetic model. Power of tests for presence of QTL was substantially reduced when the polygenic model with 3.3% of genetic variance on the chromosome was used as a null hypothesis. The ability to determine whether genetic variance on a chromosome was contributed by a single QTL of major effect or a large number of QTL with minor effects, corresponding to the infinitesimal model, was limited.

Chromosome Mapping↗
PubMed2006

Quantitative trait loci (QTL) mapping of resistance to strongyles and coccidia in the free-living Soay sheep (Ovis aries).

A genome-wide scan was performed to detect quantitative trait loci (QTL) for resistance to gastrointestinal parasites and ectoparasitic keds segregating in the free-living Soay sheep population on St. Kilda (UK). The mapping panel consisted of a single pedigree of 882 individuals of which 588 were genotyped. The Soay linkage map used for the scans comprised 251 markers covering the whole genome at average spacing of 15cM. The traits here investigated were the strongyle faecal egg count (FEC), the coccidia faecal oocyst count (FOC) and a count of keds (Melophagus ovinus). QTL mapping was performed by means of variance component analysis so that the genetic parameters of the study traits were also estimated and compared with previous studies in Soay and domestic sheep. Strongyle FEC and coccidia FOC showed moderate heritability (h(2)=0.26 and 0.22, respectively) in lambs but low heritability in adults (h(2)<0.10). Ked count appeared to have very low h(2) in both lambs and adults. Genome scans were performed for the traits with moderate heritability and two genomic regions reached the level of suggestive linkage for coccidia FOC in lambs (logarithm of the odds=2.68 and 2.21 on chromosomes 3 and X, respectively). We believe this is the first study to report a QTL search for parasite resistance in a free-living animal population and therefore may represent a useful reference for similar studies aimed at understanding the genetics of host-parasite co-evolution in the wild.

Animals↗
PubMed2004

Identification and fine mapping of quantitative trait loci for growth traits on bovine chromosomes 2, 6, 14, 19, 21, and 23 within one commercial line of Bos taurus.

We report the identification and fine mapping of QTL for birth weight (BWT), preweaning ADG (PWADG), and postweaning ADG on feed (ADGF) in a commercial line of Bos taurus using an identical-by-descent haplotype sharing method. One hundred seventy-six calves of 12 bulls (9 to 30 male calves from each sire) of the Beefbooster, Inc., M1 line were typed using 71 genetic markers from bovine chromosomes (BTA) 2, 6, 14, 19, 21, and 23 (8 to 16 markers from each chromosome). Sixteen haplotypes were found to have significant (P <0.05) associations with BWT at the comparison-wise threshold. The 16 haplotypes span 13 chromosomal regions, two on BTA 2 (9.1 to 22.5 cM and 95.0 to 100.3 cM), three on BTA 6 (8.2 to 11.8 cM, 35.5 to 49.7 cM, and 83.0 to 86.2 cM), three on BTA 14 (26.0 to 26.7 cM, 36.2 to 46.2 cM, and 52.0 to 67.7 cM), one on BTA 19 (52.0 to 52.7 cM), two on BTA 21 (9.9 to 20.4 cM and 28.2 to 46.1 cM), and two on BTA 23 (23.9 to 36.0 cM and 45.1 to 50.9 cM). Thirteen haplotypes spanning seven chromosomal regions significantly affected (P <0.05) PWADG at the comparison-wise threshold. The seven chromosomal regions include two regions on BTA 6 (11.8 to 44.2 cM and 83.0 to 86.2 cM), one on BTA 14 (26.7 to 50.8 cM), one on BTA 19 (4.8 to 15.9 cM), one on BTA 21 (9.9 to 20.4 cM), and two on BTA 23 (17.3 to 36.0 cM and 45.1 to 50.9 cM). For ADGF, 11 haplotypes were identified to have significant associations (P <0.05) at the comparison-wise threshold. The 11 haplotypes represented eight chromosomal regions, one on BTA 2 (9.1 to 22.5 cM), two on BTA 6 (49.7 to 50.1 cM and 59.6 to 63.6 cM), two on BTA 14 (17.0 to 24.0 cM and 36.2 to 46.2 cM), two on BTA 19 (52.0 to 52.7 cM and 65.1 to 65.7 cM), and one on BTA 21 (46.1 to 53.1 cM). The QTL regions identified and fine mapped in this study will provide a reference for future positional candidate gene research and marker-assisted selection of various growth traits.

Alleles↗
PubMedDate not supplied

Genome scanning by two-dimensional DNA typing: the use of repetitive DNA sequences for rapid mapping of genetic traits.

The existence of repetitive DNA sequences offers the possibility to assess the mammalian genome for individual variation in its entirety rather than at one or only a few sites. In order to fully explore the various sets of mammalian repeat sequences for this purpose, analytical tools are required which allow many if not all individual members of sets of repetitive elements to be resolved and identified in terms of location and allelic variation. We have applied and further developed an electrophoretic system, two-dimensional DNA typing, which may fulfill these requirements. The two-dimensional system combines separation of DNA fragments by size in a neutral gel, with separation by sequence composition in a denaturing gradient gel. By hybridization with minisatellite- and simple-sequence core probes and by inter-repeat polymerase chain reaction techniques, it is possible to obtain individual--and even chromosome-specific separation patterns that consist of hundreds of spots. Computerized image analysis and matching of such spot patterns allows the rapid assessment of multiple polymorphisms, spread over the genome, to monitor genetic variability in populations. When coupled to databases of polymorphic DNA markers with a known genomic location, two-dimensional DNA typing can greatly accelerate the mapping of genetic traits in humans, animals, and plants.

Alleles↗
PubMed2000

Genetic mapping of quantitative trait loci influencing left ventricular mass in rats.

High blood pressure is the leading cause of left ventricular hypertrophy (LVH); however, not all hypertensive patients develop LVH. Genetic factors are important in the development of LVH. With the use of F2 male rats from spontaneously hypertensive rats and Lewis rats, we performed a study to identify the quantitative trait loci (QTL) that influence left ventricular mass (LVM). Mean arterial pressure (MAP) was measured by the direct intra-arterial method in conscious animals, and LVM was determined at 24 wk of age. QTL analysis was done using 160 microsatellite markers for a genome-wide scan. Two loci that influenced body weight-adjusted LVM with logarithm of the odds scores >3.4 were found. One locus on chromosome 17 influenced LVM independently of MAP. Another locus on chromosome 7 influenced LVM and MAP. These findings indicate not only the existence of a gene on chromosome 7 that influences LVM in a manner dependent on blood pressure but also the existence of a gene on chromosome 17 that influences LVM independently of blood pressure.

Animals↗
PubMed1997

Map-based quantitative trait locus identification.

Poultry gene mappers chose microsatellites as the main source of genetic markers for poultry genome mapping, similar to the marker type used for other farm animals, laboratory animals, and humans. Optimal strategies for applying DNA markers in poultry populations are discussed, including the number of markers to be used, genome representation, population structure, choice of markers, population size, statistical stringency for association between markers and quantitative trait loci (QTL), and biological verification of a linkage. It is shown that an efficient strategy should be based on a combination of a low stringent statistical test for the existence of linkage between a marker and QTL and an appropriate genetic test for the discrimination between true and false linkage. The source of the genetic variation to be used is discussed and, as an illustration, three types of resource populations are presented. The informativeness of different matings using various genotypes of the parents are considered and it appears that selection of markers based on the heterozygosity of the sire is the most efficient marker screening approach.

Animals↗
PubMed2002

Mapping of quantitative trait loci controlling broomrape (Orobanche crenata Forsk.) resistance in faba bean (Vicia faba L.).

Orobanche crenata Forsk. is a root parasite that produces devastating effects on many crop legumes and has become a limiting factor for faba bean production in the Mediterranean region. The efficacy of available control methods is minimal and breeding for broomrape resistance remains the most promising method of control. Resistance seems to be scarce and complex in nature, being a quantitative characteristic difficult to manage in breeding programmes. To identify and map the QTLs (quantitative trait loci) controlling the trait, 196 F2 plants derived from the cross between a susceptible and a resistant parent were analysed using isozymes, RAPD, seed protein genes, and microsatellites. F2-derived F3 lines were studied for broomrape resistance under field conditions. Of the 130 marker loci segregating in the F2 population, 121 could be mapped into 16 linkage groups. Simple interval mapping (SIM) and composite interval mapping (CIM) were performed using QTL Cartographer. Composite interval mapping using the maximum number of markers as cofactors was clearly the most efficient way to locate putative QTLs. Three QTLs for broomrape resistance were detected. One of the three QTLs explained more than 35% of the phenotypic variance, whereas the others accounted for 11.2 and 25.5%, respectively. This result suggests that broomrape resistance in faba bean can be considered a polygenic trait with major effects of a few single genes.

Base Sequence↗
PubMed2000

Testing the robustness of the new Haseman-Elston quantitative-trait loci-mapping procedure.

Variance components (VC) techniques have emerged as among the more powerful methods for detection of quantitative-trait loci (QTL) in linkage analysis. Allison et al. found that, with particularly marked leptokurtosis in the phenotypic distribution and moderate-to-high residual sibling correlation, maximum likelihood (ML) VC methods may produce a severe excess of type I errors. The new Haseman-Elston (NHE) method is a least-squares-based VC method for mapping of QTL in sib pairs (Elston et al.). Using simulation, we investigate the robustness of the NHE to marked nonnormality, by means of the same distributions and worst-case conditions identified by Allison et al. for the ML approach (i.e., 100 pairs; high residual sibling correlation). Results showed that, when marked nonnormality is present, the NHE can be used without severe type I error-rate inflation, even at very small alpha levels.

Chromosome Mapping↗
PubMed2003

Mapping QTL for traits associated with resistance to ferrous iron toxicity in rice (Oryza sativa L.), using japonica chromosome segment substitution lines.

A mapping population of 66 japonica chromosome segment substitution lines (CSSLs) in indica genetic background, derived from a cross between a japonica variety Asominori and an indica variety IR24 by the single-seed descent, backcrossing and marker-assisted selection, was used to detect quantitative trait loci (QTLs) for leaf bronzing index (LBI), stem dry weight (SDW), plant height (PH), root length (RL) and root dry weight (RDW) under Fe2+ stress condition in rice. Two parents and 66 japonica CSSLs were phenotyped for the traits by growing them in Fe2+ toxicity nutrient solution. A total of fourteen QTLs were detected on chromosome 3, 6, 7, 9, 11 and 12, respectively, with LOD of QTLs ranging from 2.72 to 6.63. Three QTLs controlling LBI were located at the region of C515-XNpb279, R2638-C1263 and G1465-C950 on chromosome 3, 9 and 11, their contributions to whole variation were 16.45%, 11.16% and 28.02%, respectively. Comparing with the other mapping results, the QTL for LBI located at the region of C515-XNpb279 on chromosome 3 was identical with the QTL for chlorophyll content on a rice function map. The results indicated that ferrous iron toxicity of rice is characterized by bronzing spots on the lower leaves, which spread over the whole leaves, causing the lower leaves to turn dark gray and to product chlorophyll catabolites or derivatives which reduce cytotoxicity of some heavy metals, such as ferrous iron. Furthermore, the QTL for LBI, SDW and RDW located at the region of G1465-C950 on chromosome 11 is a major QTL. Whether the QTL for SDW, PH, RL and RDW at the region of XNpb386-XNpb342 on chromosome 6 is associated with resistance to ferrous iron toxicity need further studies. Our goal is to identify breeding materials for resistance to Fe2+ toxicity through marker-assisted selection based on the detected markers.

Chromosome Mapping↗