Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “quantitative trait”

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 1,009 records · Page 56Linked to original sources
PubMed2003

The EIM algorithm in the joint segregation analysis of quantitative traits.

In this article, a new algorithm for obtaining the maximum likelihood estimators (MLEs) of parameters in the joint segregation analysis (JSA) of multiple generations of P1, F1, P2, F2 and F2:3 (MG5) for quantitative traits was set up. Firstly, owing to the fact that the component variance of the heterogeneous genotype in F2:3 included both the first-order genetic parameters (denoted by the means of distributions) and the second-order parameters, a simple closed form for the MLEs of the means of component distributions did not exist while the expectation and maximization (EM) algorithm was used. To simplify the estimation of parameters, the first partial derivative of the above variance on the mean in the sample log-likelihood function was omitted. However, this would be remedied by the iterated method. Then, variances of component distributions for segregating populations were partitioned into major-gene, polygenic and environmental variances so that the generally iterated formulae for estimating the means as well as polygenic and environmental variances of component distributions in the maximization step (M-step) of the EM algorithm were obtained. Therefore, the EM algorithm for estimating parameters in the JSA model for the MG5 was simplified. This is called the expectation and iterated maximization (EIM) algorithm. Finally, an example of the inheritance of the resistance of soybean to beanfly showed that the results of mixed inheritance analysis in this paper coincided with those in both Wang & Gai (2001) and Wei et al. (1989), so the EIM algorithm was appropriate.

Algorithms↗
PubMed2003

Quantitative trait loci for lodging resistance, plant height and partial resistance to mycosphaerella blight in field pea (Pisum sativum L.).

With the development of genetic maps and the identification of the most-likely positions of quantitative trait loci (QTLs) on these maps, molecular markers for lodging resistance can be identified. Consequently, marker-assisted selection (MAS) has the potential to improve the efficiency of selection for lodging resistance in a breeding program. This study was conducted to identify genetic loci associated with lodging resistance, plant height and reaction to mycosphaerella blight in pea. A population consisting of 88 recombinant inbred lines (RILs) was developed from a cross between Carneval and MP1401. The RILs were evaluated in 11 environments across the provinces of Manitoba, Saskatchewan and Alberta, Canada in 1998, 1999 and 2000. One hundred and ninety two amplified fragment length polymorphism (AFLP) markers, 13 random amplified polymorphic DNA (RAPD) markers and one sequence tagged site (STS) marker were assigned to ten linkage groups (LGs) that covered 1,274 centi Morgans (cM) of the pea genome. Six of these LGs were aligned with the previous pea map. Two QTLs were identified for lodging resistance that collectively explained 58% of the total phenotypic variation in the mean environment. Three QTLs were identified each for plant height and resistance to mycosphaerella blight, which accounted for 65% and 36% of the total phenotypic variation, respectively, in the mean environment. These QTLs were relatively consistent across environments. The AFLP marker that was associated with the major locus for lodging resistance was converted into the sequence-characterized amplified-region (SCAR) marker. The presence or absence of the SCAR marker corresponded well with the lodging reaction of 50 commercial pea varieties.

Ascomycota↗
PubMed2004

A follow-up linkage study for quantitative trait loci contributing to obesity-related phenotypes.

We have recently reported a whole-genome scan in a sample of 630 subjects from 53 extended pedigrees, in which several genomic regions that may contain quantitative trait loci (QTLs) for obesity were suggested. In the present study, with an attempt to confirm our previous findings, we performed a follow-up linkage study in an expanded sample of 79 pedigrees with 1816 subjects (including expanded previous 53 pedigrees and 26 newly recruited pedigrees containing 1058 subjects). A new set of microsatellite markers spanning previously identified regions were selected, with the average genomic distance narrowed from approximately 10 cM to approximately 5 cM in this study. Using a variance component method, we performed two- and multipoint linkage analyses in the following three sample sets: expanded previous 53 pedigrees (758 subjects), 26 new pedigrees, and 79 total pedigrees. For body mass index, analyses of the expanded 53 pedigrees attained a LOD score of 2.32 near marker D1S468 in two-point analysis and a maximum LOD score (MLS) of 2.21 in multipoint analysis; 2q14 near marker D2S347 attained a LOD score of 3.42 in two-point analysis and a MLS of 3.93 in multipoint analysis. The linkage peaks at 1p36 and 2q14 were further supported in the analyses of all 79 pedigrees, with multipoint MLS being 1.38 and 0.90, respectively. For fat mass, genomic region 6q27 achieved a LOD score of 1.24 in two-point analysis and an MLS of 0.92 in multipoint analysis in all 79 pedigrees. Our data support that 1p36, 2q14, and 6q27 are promising regions that may harbor QTLs for obesity phenotypes.

Adult↗
PubMed1998

The accuracy of marker-assisted selection for quantitative traits within populations in linkage equilibrium.

Using the concept of conditional coancestry, given observed markers, an explicit expression of the accuracy of marker-based selection is derived in situations of linkage equilibrium between markers and quantitative trait loci (QTL), for the general case of full-sib families nested within half-sib families. Such a selection scheme is rather inaccurate for moderate values of family sizes and QTL variance, and the accuracies predicted for linkage disequilibrium can never be reached. The result is used to predict the accuracy of marker-assisted combined selection (MACS) and is shown to agree with previous MACS results obtained by simulation of a best linear unbiased prediction animal model. Low gains in accuracy are generally to be expected compared to standard combined selection. The maximum gain, assuming infinite family size and all QTLs marked, is about 50%.

Genetic Linkage↗
PubMed2002

Linkage disequilibrium mapping of quantitative trait loci under truncation selection.

As a dense map of single nucleotide polymorphism (SNP) markers are available, population-based linkage disequilibrium (LD) mapping or association study is becoming one of the major tools for identifying quantitative trait loci (QTL) and for fine gene mapping. However, in many cases, LD between the marker and trait locus is not very strong. Approaches that maximize the potential of detecting LD will be essential for the success of LD mapping of QTL. In this paper, we propose two strategies for increasing the probability of detecting LD: (1) phenotypic selection and (2) haplotype LD mapping. To provide the foundations for LD mapping of QTL under selection, we develop analytic tools for assessing the impact of phenotypic selection on allele and haplotype frequencies, and LD under three trait models: single trait locus, two unlinked trait loci, and two linked trait loci with or without epistasis. In addition to a traditional chi(2) test, which compares the difference in allele or haplotype frequencies in the selected sample and population sample, we present multiple regression methods for LD mapping of QTL, and investigate which methods are effective in employing phenotypic selection for QTL mapping. We also develop a statistical framework for investigating and comparing the power of the single marker and multilocus haplotype test for LD mapping of QTL. Finally, the proposed methods are applied to mapping QTL influencing variation in systolic blood pressure in an isolated Chinese population.

Chi-Square Distribution↗
PubMed2002

A quantitative-trait locus in the human factor XII gene influences both plasma factor XII levels and susceptibility to thrombotic disease.

One approach to the identification of genetic loci that influence complex diseases is through the study of quantitative risk factors correlated with disease susceptibility. Factor XII (FXII) plasma levels, a related phenotype correlated with thrombosis, is such a risk factor. We conducted the first genomewide linkage screen to localize genes that influence variation in FXII levels. Two loci were detected: one on chromosome 5 and another on chromosome 10 (LOD scores 4.73 and 3.53, respectively). On chromosome 5, the peak LOD score occurred in the 5q33-5ter region, near the FXII gene. Addition of a 46C/T mutation in the FXII gene increased the multipoint LOD score to 10.21 (P=3.6 x 10(-12)). A bivariate linkage analysis of FXII activity and thrombosis further improved the linkage signal (LOD = 11.73) and provided strong evidence that this quantitative-trait locus (QTL) has a pleiotropic effect on the risk of thrombosis (P=.004). Linkage analysis conditional on 46C/T indicated that this mutation alone cannot explain the chromosome 5 signal, implying that other functional sites must exist. These results represent the first direct genetic evidence that a QTL in or near the FXII gene influences both FXII activity and susceptibility to thrombosis and suggest the presence of one or more still unknown functional variants in FXII.

Chromosome Mapping↗
PubMed2003

Mapping quantitative trait loci underlying appearance quality of rice grains (Oryza sativa L.).

Ninety-eight backcross inbred lines (BILs) derived from a subspecific cross of Nipponbare (japonica)/Kasalath (indica)//Nipponbare and its genetic linkage map were used to identify quantitative trait locus (QTL) controlling rice appearance quality traits such as grain length (GL), grain width (GW), length-width ratio (LWR), percentage of grains with chalkiness (PGWC), square of chalky endosperm (SCE), degree of endosperm chalkiness (DEC) and grain endosperm transparency (GET) by composite interval mapping over two years. A total of 33 QTLs were identified to be significant in at least one year for seven traits and the number of QTL for each trait ranged from four to seven, showing that appearance quality of rice grains were controlled by multigenes. The phenotypic variation explained by individual QTLs ranged from 6.2% to 15.2% for GL, 8.3% to 32.5% for GW, 6.8% to 19.8% for LWR, 6.4% to 28.5% for PGWC, 6.1% to 16.9% for SCE, 9.3% to 17.2% for DEC, and 5.6% to 25.2% for GET. The distribution of QTL were characterized by clustering with the intervals of C1488-C563 on chromosome 3, R830-R3166 and R1436-R2289 on chromosome 5, R2147-R2171 on chromosome 6 each harboring over 3 QTLs. The QTL-by-environment interactions were observed by comparing QTL mapping of the same population grown in 2 consecutive years, but were trait dependent. The QTL for GL and LWR were rather stable across years while that for PGWC, SCE and DEC were very sensitive to environments.

Chromosome Mapping↗
PubMed2006

Quantitative trait locus analysis for obesity reveals multiple networks of interacting loci.

Obesity is a highly heritable and genetically complex trait with hundreds of potential loci identified. An intercross of 513 F2 progeny between the SM/J x NZB/BINJ inbred mouse strains was generated to identify quantitative trait loci (QTL) that are involved in the weight of four fat pads: mesenteric, inguinal, gonadal, and retroperitoneal. Sex and lean body weight were treated as covariates in the analysis of these fat pads. This analysis uncoupled genetic effects related to overall body size from those influencing the adiposity of a mouse. We identified multiple significant QTL. QTL alleles associated with increased lean body weight and individual fat pad weights are contributed by the NZB background. Adiposity loci are distinct from these body size QTLs and high-adiposity alleles are contributed by the SM background. An extended network of epistatic QTL is also observed. A QTL on Chr 19 is the center of a network of eight interacting QTL, Chr 4 is the center of six, and Chr 17 the center of four interacting QTL. We conclude that interacting networks of multiple genes characterize the regulation of fat pad depots and body weight. Haplotype patterns and a literature-driven approach were used to generate hypotheses regarding the identity of the genes and pathways underlying the QTL.

Animals↗
PubMed2006

Evolutionary aspects of population structure for molecular and quantitative traits in the freshwater snail Radix balthica.

Detecting the action of selection in natural populations can be achieved using the QST-FST comparison that relies on the estimation of FST with neutral markers, and QST using quantitative traits potentially under selection. QST higher than FST suggests the action of directional selection and thus potential local adaptation. In this article, we apply the QST-FST comparison to four populations of the hermaphroditic freshwater snail Radix balthica located in a floodplain habitat. In contrast to most studies published so far, we did not detect evidence of directional selection for local optima for any of the traits we measured: QST calculated using three different methods was never higher than FST. A strong inbreeding depression was also detected, indicating that outcrossing is probably predominant over selfing in the studied populations. Our results suggest that in this floodplain habitat, local adaptation of R. balthica populations may be hindered by genetic drift, and possibly altered by uneven gene flow linked to flood frequency.

Animals↗
PubMed2001

Genetic isolation of a blood pressure quantitative trait locus on chromosome 2 in the spontaneously hypertensive rat.

OBJECTIVES: Total genome scans of genetically segregating populations derived from the spontaneously hypertensive rat (SHR) and other rat models of hypertension have suggested the presence of quantitative trait loci (QTL) regulating blood pressure and cardiac mass on multiple chromosomes, including chromosome 2. The objective of the current study was to directly test for the presence of a blood pressure QTL on rat chromosome 2. DESIGN: A new congenic strain was derived by replacing a segment of chromosome 2 in the SHR between D2Rat171 and D2Arb24 with the corresponding chromosome segment from the normotensive Brown Norway rat. Arterial pressures were directly monitored in conscious rats by radiotelemetry. RESULTS: We found that the SHR congenic strain (SHR-2) carrying a segment of chromosome 2 from the Brown Norway rat had significantly lower systolic and diastolic blood pressures than the SHR progenitor strain. The attenuation of hypertension in the SHR-2 congenic strain versus the SHR progenitor strain was accompanied by significant amelioration of cardiac hypertrophy. CONCLUSIONS: These findings demonstrate that gene(s) with major effects on blood pressure exist in the differential segment of chromosome 2 trapped within the new SHR.BN congenic strain.

Animals↗
PubMed2005

Quantitative trait locus analysis using recombinant inbred intercrosses: theoretical and empirical considerations.

We describe a new approach, called recombinant inbred intercross (RIX) mapping, that extends the power of recombinant inbred (RI) lines to provide sensitive detection of quantitative trait loci (QTL) responsible for complex genetic and nongenetic interactions. RIXs are generated by producing F1 hybrids between all or a subset of parental RI lines. By dramatically extending the number of unique, reproducible genomes, RIXs share some of the best properties of both the parental RI and F2 mapping panels. These attributes make the RIX method ideally suited for experiments requiring analysis of multiple parameters, under different environmental conditions and/or temporal sampling. However, since any pair of RIX genomes shares either one or no parental RIs, this cross introduces an unusual population structure requiring special computational approaches for analysis. Herein, we propose an efficient statistical procedure for QTL mapping with RIXs and describe a novel empirical permutation procedure to assess genome-wide significance. This procedure will also be applicable to diallel crosses. Extensive simulations using strain distribution patterns from CXB, AXB/BXA, and BXD mouse RI lines show the theoretical power of the RIX approach and the analysis of CXB RIXs demonstrates the limitations of this procedure when using small RI panels.

Animals↗
PubMed2000

Quantitative trait loci (QTL) analysis in a Meishan x Göttingen cross population.

In order to locate the genetic regions in the swine genome that are responsible for economically important traits, a resource population has been constructed by mating two female Meishan pigs with a male Göttingen miniature pig. In subsequent generations, 265 F2 offspring were produced from two F1 males and 19 F1 females. The F2 offspring were scored for eight traits including growth rate, teat number, vertebra number and backfat thickness, and genotyped for 318 genetic markers spanning the swine genome. Least-square analysis revealed quantitative trait loci (QTL) effects for vertebra number on chromosomes 1 and 2; for teat number on chromosomes 1 and 7; for birth weight on chromosome 1; for average daily gain between 4 and 13 weeks of age on chromosomes 9 and 10; for backfat thickness on chromosome 7; and for backskin thickness on chromosome 3.

Animals↗
PubMed2005

Quantitative trait loci associated with seed and seedling traits in Lactuca.

Seed and seedling traits related to germination and stand establishment are important in the production of cultivated lettuce (Lactuca sativa L.). Six seed and seedling traits segregating in a L. sativa cv. Salinas x L. serriola recombinant inbred line population consisting of 103 F8 families revealed a total of 17 significant quantitative trait loci (QTL) resulting from three seed production environments. Significant QTL were identified for germination in darkness, germination at 25 and 35 degrees C, median maximum temperature of germination, hypocotyl length at 72 h post-imbibition, and plant (seedling) quality. Some QTL for germination and early seedling growth characteristics were co-located, suggestive of pleiotropic loci regulating these traits. A single QTL (Htg6.1) described 25 and 23% of the total phenotypic variation for high temperature germination in California- and Netherlands-grown populations, respectively, and was significant between 33 and 37 degrees C. Additionally, Htg6.1 showed significant epistatic interactions with other Htg QTL and a consistent effect across all the three seed production environments. L. serriola alleles increased germination at these QTL. The estimate of narrow-sense heritability (h2) of Htg6.1 was 0.84, indicating potential for L. serriola as a source of germination thermotolerance for lettuce introgression programs.

Breeding↗
PubMed1993

Theoretical basis for separation of multiple linked gene effects in mapping quantitative trait loci.

It is now possible to use complete genetic linkage maps to locate major quantitative trait loci (QTLs) on chromosome regions. The current methods of QTL mapping (e.g., interval mapping, which uses a pair or two pairs of flanking markers at a time for mapping) can be subject to the effects of other linked QTLs on a chromosome because the genetic background is not controlled. As a result, mapping of QTLs can be biased, and the resolution of mapping is not very high. Ideally when we test a marker interval for a QTL, we would like our test statistic to be independent of the effects of possible QTLs at other regions of the chromosome so that the effects of QTLs can be separated. This test statistic can be constructed by using a pair of markers to locate the testing position and at the same time using other markers to control the genetic background through a multiple regression analysis. Theory is developed in this paper to explore the idea of a conditional test via multiple regression analysis. Various properties of multiple regression analysis in relation to QTL mapping are examined. Theoretical analysis indicates that it is advantageous to construct such a testing procedure for mapping QTLs and that such a test can potentially increase the precision of QTL mapping substantially.

Chromosome Mapping↗
PubMed2000

Selective genotyping to detect quantitative trait loci for multiple traits in outbred populations.

Selective genotyping (i.e., genotyping of individuals that are extreme for a quantitative trait) has been undertaken in many studies but has usually been limited to one trait of interest. This paper outlines the implications of selective genotyping when applied to a daughter design. Formulas are presented that enable unbiased estimation of QTL effects for the selectively genotyped and correlated traits. Formulas were verified using simulation. Further, formulas are presented to enable power calculations to be undertaken for the selectively genotyped trait and correlated traits. These algorithms are demonstrated with a numerical example.

Animals↗
PubMed2000

Inheritance of partial resistance against Colletotrichum lindemuthianum in Phaseolus vulgaris and co-localization of quantitative trait loci with genes involved in specific resistance.

Anthracnose, one of the most important diseases of common bean (Phaseolus vulgaris), is caused by the fungus Colletotrichum lindemuthianum. A "candidate gene" approach was used to map anthracnose resistance quantitative trait loci (QTL). Candidate genes included genes for both pathogen recognition (resistance genes and resistance gene analogs [RGAs]) and general plant defense (defense response genes). Two strains of C. lindemuthianum, identified in a world collection of 177 strains, displayed a reproducible and differential aggressiveness toward BAT93 and JaloEEP558, two parental lines of P. vulgaris representing the two major gene pools of this crop. A reliable test was developed to score partial resistance in aerial organs of the plant (stem, leaf, petiole) under controlled growth chamber conditions. BAT93 was more resistant than JaloEEP558 regardless of the organ or strain tested. With a recombinant inbred line (RIL) population derived from a cross between these two parental lines, 10 QTL were located on a genetic map harboring 143 markers, including known defense response genes, anthracnose-specific resistance genes, and RGAs. Eight of the QTL displayed isolate specificity. Two were co-localized with known defense genes (phenylalanine ammonia-lyase and hydroxyproline-rich glycoprotein) and three with anthracnose-specific resistance genes and/or RGAs. Interestingly, two QTL, with different allelic contribution, mapped on linkage group B4 in a 5.0 cM interval containing Andean and Mesoamerican specific resistance genes against C. lindemuthianum and 11 polymorphic fragments revealed with a RGA probe. The possible relationship between genes underlying specific and partial resistance is discussed.

Chromosome Mapping↗
PubMed2003

Mapping of quantitative trait loci controlling trypanotolerance in a cross of tolerant West African N'Dama and susceptible East African Boran cattle.

Trypanosomosis, or sleeping sickness, is a major disease constraint on livestock productivity in sub-Saharan Africa. To identify quantitative trait loci (QTL) controlling resistance to trypanosomosis in cattle, an experimental cross was made between trypanotolerant African N'Dama (Bos taurus) and trypanosusceptible improved Kenya Boran (Bos indicus) cattle. Sixteen phenotypic traits were defined describing anemia, body weight, and parasitemia. One hundred seventy-seven F2 animals and their parents and grandparents were genotyped at 477 molecular marker loci covering all 29 cattle autosomes. Total genome coverage was 82%. Putative QTL were mapped to 18 autosomes at a genomewise false discovery rate of <0.20. The results are consistent with a single QTL on 17 chromosomes and two QTL on BTA16. Individual QTL effects ranged from approximately 6% to 20% of the phenotypic variance of the trait. Excluding chromosomes with ambiguous or nontrypanotolerance effects, the allele for resistance to trypanosomosis originated from the N'Dama parent at nine QTL and from the Kenya Boran at five QTL, and at four QTL there is evidence of an overdominant mode of inheritance. These results suggest that selection for trypanotolerance within an F2 cross between N'Dama and Boran cattle could produce a synthetic breed with higher trypanotolerance levels than currently exist in the parental breeds.

Anemia↗
PubMed1998

Mapping quantitative trait loci using multiple families of line crosses.

To avoid a loss in statistical power as a result of homozygous individuals being selected as parents of a mapping population, one can use multiple families of line crosses for quantitative trait genetic linkage analysis. Two strategies of combining data are investigated: the fixed-model and the random-model strategies. The fixed-model approach estimates and tests the average effect of gene substitution for each parent, while the random-model approach treats each effect of gene substitution as a random variable and directly estimates and tests the variance of gene substitution. Extensive Monte Carlo simulations verify that the two strategies perform equally well, although the random model is preferable in combining data from a large number of families. Simulations also show that there may be an optimal sampling strategy (number of families vs. number of individuals per family) in which QTL mapping reaches its maximum power and minimum estimation error. Deviation from the optimal strategy reduces the efficiency of the method.

Chromosome Mapping↗