Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “quantitative genetics”

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 1,333 records · Page 74Linked to original sources
PubMed2001

The biological basis of epistasis between quantitative trait loci for flavone and 3-deoxyanthocyanin synthesis in maize (Zea mays L.).

A major weakness in our understanding of the genetic basis of complex traits has been that of defining the extent and biological basis of epistasis. Our research group has been studying the genetic control of the accumulation of maysin, a C-glycosyl flavone, in maize, Zea mays (L.), silks. Previously, we demonstrated the importance of the p1 locus as a QTL for maysin synthesis. The p1 locus often exhibits significant epistatic interactions with other loci. We developed a mapping population, (W23al x GT119)F2, specifically designed to test whether genes in an intersecting pathway might be detected as QTLs for maysin synthesis and result in epistatic interaction effects. The a1 gene is not required for the synthesis of flavones but is required for the synthesis of 3-deoxyanthocyanins, an intersecting pathway, in maize silks. The p1 locus (P < 0.0001) was a QTL for both flavones and 3-deoxyanthocyanins. The a1 locus was also highly significant (P < 0.0001) for both traits, as was the p1 x a1 epistatic interaction (P < 0.0001). Our results demonstrate that altering the flux of biochemical intermediates between pathways may be the biological basis of major QTL effects and epistatic interactions.

Alleles↗
PubMed2002

[Marker analysis of quantitative traits in maize by ISSR-PCR].

The segregating maize population (GK26 x Mo17)F2 has been used for identification of ISSR markers able to reveal a significant difference between alleles by a quantitative index. Confidence ranges have been determined for variation in 17 quantitative traits. Variations in the traits under study correlate with the inheritance of 16 marker loci have been found. The nature of these correlations and the possibility of chromosomal mapping of genetic markers are discussed.

Crosses, Genetic↗
PubMed2026

Multilevel Exploration of Shared Genetic Architecture Between Primary Biliary Cholangitis and Four Autoimmune Diseases.

INTRODUCTION: Primary Biliary Cholangitis (PBC) frequently coexists with various autoimmune diseases, such as Multiple Sclerosis (MS), Psoriasis (PS), Rheumatoid Arthritis (RA), and Sj&#xf6;gren's Syndrome (SS). Understanding the genetic associations between these diseases is crucial for providing deeper insights into their shared pathogenic mechanisms and comorbidity patterns. METHODS: This study utilized genome-wide association study summary data of PBC and four autoimmune diseases (MS, PS, RA, and SS). A multi-stage analytical pipeline was employed to systematically investigate the genetic associations between the diseases. The analytical approach consisted of three stages: first, linkage disequilibrium score regression and high-definition likelihood methods were applied to estimate overall genetic correlations between the diseases; second, local genetic correlation analysis was conducted to pinpoint genetic signals in specific chromosomal regions; third, conditional/conjunctional false discovery rate (cond/conjFDR) algorithms were used to quantitatively assess genetic overlap and identify shared susceptibility loci. RESULTS: Genome-wide analysis revealed significant genetic associations between PBC and the four autoimmune diseases (MS, PS, RA, and SS). Regional analysis showed local genetic correlations across various chromosomal segments. cond/conjFDR analysis confirmed genetic intersections among the diseases and identified several critical genetic polymorphic loci that influence disease susceptibility. DISCUSSION: This study comprehensively delineates the shared genetic architecture underlying PBC and four autoimmune diseases through integrative analyses of multiple genome-wide approaches. The results highlight strong genetic correlations, particularly between PBC and MS, PS, RA, and SS, and identify key shared susceptibility genes, including CLEC16A, CD58, CD86, STAT4, IRF5, TYK2, and TNFAIP3, which collectively mediate immune dysregulation through autophagy, cytokine signaling, and NF-&#x3ba;B pathways. These findings not only extend current understanding of the molecular mechanisms driving autoimmune comorbidity but also provide potential genetic targets for future functional validation and therapeutic exploration. CONCLUSION: This study provides comprehensive genomic evidence for the genetic connections between PBC and the four autoimmune diseases (MS, PS, RA, and SS), offering valuable insights into the shared pathological mechanisms underlying their comorbidities.

Humans↗
PubMed2002

[Analysis of correlation between body length and genetic polymorphism for loci ESTD-1 and IDHP-3 in the Atlantic salmon Salmo salar].

Correlation between body length and characteristics of genetic polymorphism for loci Me-2, IDHP-3, ESTD-1, and AAT-2 were studied in the Atlantic salmon Salmo salar. The study was based on data on genetic variation in more than 4000 fish grown at the Kandalaksha Hatchery. Of four loci studied, loci ESTD-1 and IDHP-3 were distinguished by the fact that they can be confidently considered body-length markers in the Atlantic salmon. Analysis of mean locus heterozygosity indicates a disturbance of the mechanism of negative heterosis that is characteristic of natural populations. This presumably reflects a change in the genetic diversity of the Atlantic salmon under the influence of breeding.

Alleles↗
PubMed1999

Genetic variation maintained in multilocus models of additive quantitative traits under stabilizing selection.

Stabilizing selection for an intermediate optimum is generally considered to deplete genetic variation in quantitative traits. However, conflicting results from various types of models have been obtained. While classical analyses assuming a large number of independent additive loci with individually small effects indicated that no genetic variation is preserved under stabilizing selection, several analyses of two-locus models showed the contrary. We perform a complete analysis of a generalization of Wright's two-locus quadratic-optimum model and investigate numerically the ability of quadratic stabilizing selection to maintain genetic variation in additive quantitative traits controlled by up to five loci. A statistical approach is employed by choosing randomly 4000 parameter sets (allelic effects, recombination rates, and strength of selection) for a given number of loci. For each parameter set we iterate the recursion equations that describe the dynamics of gamete frequencies starting from 20 randomly chosen initial conditions until an equilibrium is reached, record the quantities of interest, and calculate their corresponding mean values. As the number of loci increases from two to five, the fraction of the genome expected to be polymorphic declines surprisingly rapidly, and the loci that are polymorphic increasingly are those with small effects on the trait. As a result, the genetic variance expected to be maintained under stabilizing selection decreases very rapidly with increased number of loci. The equilibrium structure expected under stabilizing selection on an additive trait differs markedly from that expected under selection with no constraints on genotypic fitness values. The expected genetic variance, the expected polymorphic fraction of the genome, as well as other quantities of interest, are only weakly dependent on the selection intensity and the level of recombination.

Alleles↗
PubMed2001

Variation, selection and evolution of function-valued traits.

We describe an emerging framework for understanding variation, selection and evolution of phenotypic traits that are mathematical functions. We use one specific empirical example--thermal performance curves (TPCs) for growth rates of caterpillars - to demonstrate how models for function-valued traits are natural extensions of more familiar, multivariate models for correlated, quantitative traits. We emphasize three main points. First, because function-valued traits are continuous functions, there are important constraints on their patterns of variation that are not captured by multivariate models. Phenotypic and genetic variation in function-valued traits can be quantified in terms of variance-covariance functions and their associated eigenfunctions: we illustrate how these are estimated as well as their biological interpretations for TPCs. Second, selection on a function-valued trait is itself a function, defined in terms of selection gradient functions. For TPCs, the selection gradient describes how the relationship between an organism's performance and its fitness varies as a function of its temperature. We show how the form of the selection gradient function for TPCs relates to the frequency distribution of environmental states (caterpillar temperatures) during selection. Third, we can predict evolutionary responses of function-valued traits in terms of the genetic variance-covariance and the selection gradient functions. We illustrate how non-linear evolutionary responses of TPCs may occur even when the mean phenotype and the selection gradient are themselves linear functions of temperature. Finally, we discuss some of the methodological and empirical challenges for future studies of the evolution of function-valued traits.

Animals↗
PubMed2005

Dynamics of a quantitative character subject only to stabilising selection.

The implications of stabilising selection on a quantitative trait, in the absence of other evolutionary forces, are theoretically investigated in a randomly mating population. The dynamics of various statistics that describe the alleles contributing to the trait are determined and used to infer the behaviour of the trait. Dynamical solutions of the distribution of allelic effects and the distribution of the trait are found when all initial distributions of allelic effects are Gaussian and linkage disequilibria are neglected. Some results for the behaviour of the mean and the variance of genotypic effects of the population, when subject to a moving optimum, are derived. When the initial distributions of allelic effects are not Gaussian, but possess a small asymmetry, the mean and the variance of the allelic effects differ only slightly from the Gaussian results. By contrast, the third central moments of allelic effects, are, at all loci, strictly zero in the Gaussian case but are generally non-zero for non-symmetric initial distributions. To leading order in a quantitative measure of the asymmetry of the distribution, we determine the third central moment of allelic effects.

Alleles↗
PubMed2026

Tonsillar expression quantitative trait loci verify and expand genetic contributors to childhood atopic diseases.

BACKGROUND: The spectrum of causal variants, mechanisms, and immunologic gene networks that influence pediatric atopic traits is not completely understood. Human genetic variation associated with transcript abundance (expression quantitative trait loci [eQTLs]) can help to advance our understanding, yet prior work has focused on profiling immune cell populations collected from peripheral blood primarily in adult populations, leaving tissue-resident lymphocytes collected from children uncharacterized. OBJECTIVE: We sought to characterize gene expression of 4 populations of tonsil-derived immune cell types collected from pediatric patients. METHODS: We collected naive B, germinal center B, naive T, and T follicular helper cells from the discarded tonsils of 103 children across development (age range 1-19). Following genotyping and RNA sequencing of samples, we performed differential expression and eQTL analysis, then statistically linked eQTL signals to relevant atopic traits via colocalization. RESULTS: We found differentially expressed genes across cell types and identified 13,393 expression genes (eGenes) (1,793 eGenes not previously reported in similar datasets) influenced by 27,603 eQTLs (5,199 eQTLs not previously reported). We linked eQTLs to associations identified in pediatric and adult asthma and atopy traits, nominating 78 eGenes including TRAF3, ZBTB10, and JAZF1 in disease-relevant cell types. CONCLUSIONS: Our freely available resource exemplifies the importance of discovery in native tissues and across human development.

Expression quantitative trait locus↗
PubMed1985

The genetics of schizophrenia: new perspectives.

Despite the evidence for genetic factors in schizophrenia, the underlying hereditary defect is unknown. The author reviews recent advances in genetic research methodologies and discusses their strengths and limitations. He concludes that in the face of genetic heterogeneity current models of segregation analysis are not likely to unravel the mode of inheritance of schizophrenia. The author underscores the potential contribution of both molecular genetics (as a means to generate DNA markers) and studies with biologic vulnerability traits to identifying and quantitating the genetic component in the transmission of schizophrenia.

Chromosome Mapping↗
PubMed1998

Construction of a rat genetic map by using randomly amplified microsatellite polymorphism (RAMP) markers.

Many rat strains have been employed in the genetic study of quantitative traits such as blood pressure. In such genetic studies, it is essential to prepare rat genetic maps fine enough to identify the genes regulating quantitative traits. However, it is not an easy task to isolate a sufficient number of genetic markers polymorphic between a particular pair of rat strains. In this study, we applied the randomly amplified microsatellite polymorphism (RAMP) method, a simple method to identify co-dominant markers (Wu et al. Nucleic Acids Res 22, 3257, 1994), to isolate markers polymorphic between the stroke-prone spontaneously hypertensive rat and the Wistar-Kyoto rat, a genetically hypertensive strain and its normotensive control strain, which share a common genetic background. We successfully identified 111 RAMP markers distributed throughout the rat genome after screening 3046 sets of primers. We also showed that we could isolate ordinary simple-sequence-length-polymorphism markers by cloning RAMP markers. The RAMP method is a simple and efficient way to identify co-dominant genetic markers on mammalian genomes.

Animals↗
PubMed2005

Genetic heterogeneity, modifier genes, and quantitative phenotypes in psychiatric illness: searching for a framework.

Schizophrenia has long been thought to be clinically heterogeneous. A range of studies suggests that this is due to genetic heterogeneity. Some clinical features, such as negative symptoms, are associated with a greater risk of illness in relatives. Affected sibling pairs are correlated for clinical and course features as well as subforms of illness, and twin studies suggest that this is due to genetic factors. This is further supported by findings that subjects from families linked to some chromosomal regions may differ clinically from those from unlinked families. Moreover, some genes may affect clinical features without altering susceptibility (ie are modifier genes). High-risk genotypes may have quantitative, rather than categorical effects, and may influence milder or subclinical phenotypes. Another recent finding is that nonpsychotic relatives may have personality features that resemble those of their affected relatives. These findings taken together suggest that there may be several classes of gene action in schizophrenia: some genes may influence susceptibility only, others may influence clinical features only, and still others may have a mixed effect. Furthermore, subsets of these classes may affect personality and other traits in nonpsychotic relatives. Understanding these classes of gene action may help guide the design of linkage and association studies that have increased power. We describe five classes of genes and their predictions of the outcomes of family, twin, and several types of linkage studies. We go on to explore how these predictions can in turn be used to aid in the design of linkage studies.

Genetic Linkage↗
PubMed2004

[Two approaches of quantitative-trait linkage analysis].

ln this article, we discussed two model-free methods for detecting genetic linkage for quantitative traits, Haseman-Elston regression approach and variance components approach. The former is a regression approach for detecting linkage based on the squared difference or squared sums in quantitative trait values of sib-pairs and their estimated marker IBD scores. The latter can jointly model covariate effects along with variance components, including genetic component and non-genetic sources of variability. We have outlined the model assumption, the algorithm and the extensions for the both methods.

Computer Simulation↗
PubMed2005

Comparison of variable number tandem repeat and short tandem repeat genetic markers for qualitative and quantitative chimerism analysis post allogeneic stem cell transplantation.

BACKGROUND: Analysis of donor chimerism has become a routine procedure for the documentation of engraftment after allogeneic hematopoietic stem cell transplantation. Quantitative analysis of chimerism kinetics has been shown to predict graft failure or relapse. In this study, we compared the use of variable number tandem repeats (VNTR) and short tandem repeats (STR) as polymorphic genetic markers in chimerism analysis. This study included qualitative and quantitative assessment of both techniques to assess informative yield and sensitivity. PATIENTS AND METHODS: We analyzed 206 samples representing 40 transplant recipients and their HLA-identical sibling donors. A panel of six VNTR loci, 15 STR loci and 1 sex chromosome locus was used. Amplified VNTR products were visualized in an ethidium bromide-stained gel. STR loci were amplified using fluorescent primers, and the products were analyzed by capillary electrophoresis. RESULTS: VNTR and STR analysis gave comparable qualitative results in the majority of cases. The incidence of mixed chimerism (MC) by STR analysis was 45% compared to 32% in cases evaluated by VNTR analysis. STR markers were more informative; several informative loci could be identified in all patients. Unique alleles for both patient and donor could be identified in all patients by STR versus 32/40 by VNTR analysis. The STR markers were also more sensitive in the detection of chimerism. The size of VNTR alleles and differences between the size of donor and recipient VNTR alleles affected the sensitivity of detection. With both techniques, quantitative assessment of chimerism showed some discrepancies between the estimated and the calculated percentage of donor DNA. Discordance between the two estimates was observed in 8/19 patients with MC. However, sequential monitoring of the relative band intensity of VNTR alleles offered some insight into the direction of change in engraftment over time. CONCLUSION: The higher yield of informative loci with STR and the automated measurement of amplified STR 103 products offered the advantages of more rapid and accurate quantitative assessment of chimerism. The choice between these two techniques depends on the need for quantitative or qualitative information, the availability of equipment, and the cost.

Chimerism↗
PubMed1983

Similarity of genetic distance determined from DNA thermal denaturation profiles to standard estimates of bacteriophage relatedness.

High resolution thermal denaturation profiles of a series of potentially related bacteriophages of Bacillus subtilis contain a multitude of distinctive features that permit them to be divided into at least four groups. In addition, the profiles can be used to derive the quantitative parameter, genetic distance, defined by Soumpasis (Soumpasis, D. (1980) J. Theor. Biol. 86, 137-147). Both the quantitative and the qualitative intercomparisons of profiles are in general agreement with the results of standard techniques for estimating genetic relatedness.

Bacillus subtilis↗
PubMed2001

Influence of ethanol on thermoregulation: mapping quantitative trait loci.

The genetic basis for the effects of ethanol on thermoregulation was investigated by utilizing recombinant inbred mouse strains from C57BL/6J and DBA/2J progenitor strains. Changes in core body temperature (T(c)) and the degree of fluctuation of T(c) were monitored in male mice following the administration of ethanol in an environment with cyclic changes in ambient temperature (T(a)). Changes in T(c) were utilized to assess ethanol-induced effects on regulated T(c), whereas fluctuations in T(c) were utilized to assess thermoregulatory disruption. Ethanol was administered intraperitoneally at 1.5, 2.5, and 3.5 g/kg for all strains. Change in T(c) and increase in tail temperature were also evaluated at 2.5 g/kg ethanol in a constant T(a) of 26 degrees C. Associations between the measured physiological responses and previously mapped genetic markers were used to identify quantitative trait loci (QTLs). This established probable chromosome locations for a number of genes for the responses. To our knowledge, this is the first report of QTLs that underlie changes in regulation as well as the disruption of a physiological regulatory system.

Animals↗
PubMed2000

Effect of genetic cross on the detection of quantitative trait loci and a novel approach to mapping QTLs.

A genome-wide scan was conducted in two F(2) intercrosses, C57BL/6J (B6)xDBA/2J (D2) and BALB/cJ (C)xLP/J (LP), for three different phenotypes: basal locomotor activity, ethanol-induced locomotor activity, and haloperidol-induced catalepsy. For basal activity, significant quantitative trait loci (QTLs, LOD> or =4.3) were detected on chromosomes 9 and 19 for the CxLP intercross and chromosome 1 for the B6xD2 intercross. Significant QTLs for ethanol-induced activation were detected on chromosome 6 for the CxLP intercross, and on chromosomes 1 and 2 for the B6xD2 intercross. For haloperidol-induced catalepsy, significant QTLs were detected on chromosome 14 (two different QTLs) in the CxLP intercross, and chromosomes 1 and 9 in the B6xD2 intercross. These data illustrate the importance of the genetic cross for QTL detection. Finally, the data reported here, and elsewhere, are also used to demonstrate a novel approach to QTL detection and localization.

Animals↗