Variation at the apolipoprotein (apo) AI-CIII-AIV gene cluster and apo B gene loci is associated with lipoprotein and apolipoprotein levels in Italian children.

We have used RFLPs of the apolipoprotein (apo) B gene and apo AI-CIII-AIV gene cluster to estimate the genetic contribution of variation at these loci to the variability of plasmid lipid, lipoprotein, and apolipoprotein levels in 209 children from Sezze in central Italy. The sample was randomly divided into group I (107 children) and group II (102 children). Four site polymorphisms (PvuII, XbaI, MspI, and EcoRI) of the apo B gene and five site polymorphisms (XmnI, PstI, SstI, PvuII-CIII, and PvuII-AIV) of the apo AI-CIII-AIV gene cluster were examined in group I children. After adjustment for gender, age, and body-mass index, polymorphisms at both gene loci (PvuII-B, PvuII-CIII, and PvuII-AIV) were associated with significant effects on the levels of plasma apo AI, apo B, or high-density lipoprotein-cholesterol. RFLPs that showed significant effects in group I were genotyped in group II. All three polymorphisms were associated with similar effects on apolipoprotein levels, though for all RFLPs the magnitude of the effects was smaller in the group II children and only statistically significant for the effect of the PvuII-B genotype on apo AI levels. In the total sample of 209 children 7.4% of the sample variance in apo AI levels was explained by variation associated with the apo B PvuII-B RFLP. In addition, the PvuII-B RFLP was associated with significant effects on plasma apo B levels and explained 5.7% of the sample variance. The PvuII-CIII and PvuII-AIV polymorphisms were both associated with differences in apo AI levels, explaining 3.7%-5.7% of the sample variance. Taken together, the three PvuII polymorphisms explained 17.7% of the phenotypic variance in apo AI levels. There was significant evidence for an effect of nonlinearity of the PvuII-CIII genotypes on apo AI levels, with the individuals heterozygous for the polymorphism having the highest apo AI levels. No evidence of interaction between genotype and gender, age, and body-mass index was shown by covariance analysis. The molecular explanation of this effect is unclear. Our data show that variation at both the apo AI-CIII-AIV and apo B loci are associated with lipoprotein and apolipoprotein levels in this sample of Italian children.     

DNA polymorphisms of the apolipoprotein AII and AI-CIII-AIV genes: a study in men selected for differences in high-density-lipoprotein cholesterol concentration.

We have investigated the frequencies of RFLPs of the apolipoprotein (apo) AII gene and of the apo AI-CIII-AIV gene cluster in 109 men, selected from a random sample of 1,910 men aged 45-59 years, to cover a wide range of plasma high-density-lipoprotein (HDL)-cholesterol concentration. There was no significant difference in apo AI or apo AII RFLP allele frequency between groups of individuals with high and low HDL-cholesterol concentration. However, the apo AI PstI RFLP showed an association with genetic variation determining the plasma concentration of apo AI in this sample. Genetic variation in the apo AI-CIII-AIV gene region, as defined by haplotypes, accounted for 16% of the phenotypic variance in the apo AI concentration and for 8% of the phenotypic variance in HDL-cholesterol concentration. There was no significant association between alleles of the apo AII MspI RFLP and genetic variation determining apo AII or HDL concentration. The data demonstrate that genetic variation in the apo AI-CIII-AIV gene cluster is involved in determining the serum concentration of apo AI in this sample of clinically well individuals.     

Polymorphisms in the apolipoprotein (apo) AI-CIII-AIV gene cluster: detection of genetic variation determining plasma apo AI,apo CIII and apo AIV concentrations

We have examined the associations between levels of plasma apolipoprotein (apo) AI, apo CIII and apo AIV and genetic variation in the apo AI-CIII-AIV gene cluster in 162 boys and young men from Belgium aged from 7 to 23 years. Genotypes were determined for six restriction enzymes XmnI, PstI, SstI, PvuIIA-CIII, PvuIIB-AIV and XbaI, and for the G to A substitution at -75 bp in the 5' region of the apo AI gene. The polymorphism most strongly associated with apo AI levels was the G to A substitution (P = 0.025, R2 x 100 = 3.6%) confirming previous observations. The polymorphism most strongly associated with apo CIII levels was that of PvuIIA-CIII (P = 0.023, R2 x 100 = 2.9%) in the apo CIII gene. This novel association must be interpreted with caution until it has been confirmed in an independent sample. The polymorphism associated with the largest effect on apo AIV levels was that detected with XbaI in the apo AIV gene, but this association was not statistically significant. Previously reported associations between the SstI polymorphism and triglyceride levels, and between the PstI polymorphism and apo AI levels, were weakly detected in the present sample. Our results show that variation associated with some of the polymorphisms in the apo AI-CIII-AIV cluster makes a small, but statistically significant, contribution to the determination of apo AI and apo CIII levels in this sample of young men and boys. These observations may, in part, explain reported associations between polymorphisms in this gene cluster, differences in plasma lipid and lipoprotein levels, and prevalence of coronary artery disease.     

Identification and characterization of polymorphisms at the HAS alpha1-acid glycoprotein (ORM*) gene locus in Caucasians

Human alpha(1)-acid glycoprotein (AGP) or orosomucoid (ORM) is a major acute phase protein that is thought to play a crucial role in maintaining homeostasis. Human AGP is the product of a cluster of at least two adjacent genes located on HSA chromosome 9. Using a range of restriction endonucleases we have investigated DNA variation at the locus encoding the AGP genes in a group of healthy Caucasians. Polymorphisms were identified using BamHI, EcoRI, BglII, PvuII, HindIII, TaqI and MspI. Nonrandom associations were found between the BamHI, EcoRI and BglII RFLPs. The RFLPs detected with PvuII, TaqI and MspI were all located in exon 6 of both AGP genes. The duplication of an AGP gene was observed in 11% of the individuals studied and was in linkage disequilibrium with the TaqI RFLP. The identification and characterization of these polymorphisms should prove useful for other population and forensic studies.     

Phenotypic variation and natural selection at catsup, a pleiotropic quantitative trait gene in Drosophila

Quantitative traits are shaped by networks of pleiotropic genes . To understand the mechanisms that maintain genetic variation for quantitative traits in natural populations and to predict responses to artificial and natural selection, we must evaluate pleiotropic effects of underlying quantitative trait genes and define functional allelic variation at the level of quantitative trait nucleotides (QTNs). Catecholamines up (Catsup), which encodes a negative regulator of tyrosine hydroxylase , the rate-limiting step in the synthesis of the neurotransmitter dopamine, is a pleiotropic quantitative trait gene in Drosophila melanogaster. We used association mapping to determine whether the same or different QTNs at Catsup are associated with naturally occurring variation in multiple quantitative traits. We sequenced 169 Catsup alleles from a single population and detected 33 polymorphisms with little linkage disequilibrium (LD). Different molecular polymorphisms in Catsup are independently associated with variation in longevity, locomotor behavior, and sensory bristle number. Most of these polymorphisms are potentially functional variants in protein coding regions, have large effects, and are not common. Thus, Catsup is a pleiotropic quantitative trait gene, but individual QTNs do not have pleiotropic effects. Molecular population genetic analyses of Catsup sequences are consistent with balancing selection maintaining multiple functional polymorphisms.     

Relationships between DNA and protein polymorphisms of apolipoprotein B

Summary The associations between four restriction fragment length polymorphisms (RFLPs) of the gene for human apolipoprotein B (apo B) and five antigen group (Ag) protein-polymorphisms of apo B have been investigated in 24 unrelated Finnish individuals. In this sample a complete correlation exists between the EcoRI RFLP and the Ag(t/z) polymorphism. There is strong association between the alleles of the XbaI RFLP and Ag(c/g) and a weaker one of the same XbaI site with Ag(x/y). Linkage disequilibrium is observed between the PvuII RFLP and the Ag(a₁/d) polymorphism. These associations confirm that the Ag variants are true protein sequence polymorphisms of apo B.     

Genetic analysis of sexual dimorphism in serum apo AI and HDL-C concentrations in baboons

Sexual dimorphism is evident in many quantitative genetic traits, and there has been much speculation on the evolution of primate sexual dimorphism. Morphological characters have been the main focus of attention, while sexual dimorphism in physiological quantitative traits has been neglected. In either case, the genetic basis of primate sexual dimorphism has received little attention. This study characterizes genotype by sex (GxS) interactions in two physiological traits, serum apolipoprotein AI (apo AI) and high density lipoprotein cholesterol (HDL-C) concentrations, in baboons fed two different diets, a basal diet and a high cholesterol saturated fat (HCSF) diet. A GxS interaction effect on a trait indicates a heritable component of male/female differences in that trait. Using maximum likelihood methods, eight different quantitative genetic models were evaluated. Significant GxS interactions were found for serum apo AI and HDL-C concentrations on the basal diet. GxS interactions were suggested for serum apo AI and HDL-C concentrations on the HCSF diet, but they were not statistically significant. These results reveal that sexual dimorphisms in serum apo AI and HDL-C concentrations in baboons are heritable, with heritabilities that are influenced by diet. © 1992 Wiley-Liss, Inc.     

QTL analysis of white blood cell, platelet and red blood cell-related traits in an F2 intercross between Landrace and Korean native pigs

Haematological traits play important roles in disease resistance and defence functions. The objective of this study was to locate quantitative trait loci (QTL) and the associated positional candidate genes influencing haematological traits in an F₂ intercross between Landrace and Korean native pigs. Eight blood‐related traits (six erythrocyte traits, one leucocyte trait and one platelet trait) were measured in 816 F₂ progeny. All experimental animals were genotyped with 173 informative microsatellite markers located throughout the pig genome. We report that nine chromosomes harboured QTL for the baseline blood parameters: genomic regions on SSC 1, 4, 5, 6, 8, 9, 11, 13 and 17. Eight of twenty identified QTL reached genome‐wide significance. In addition, we evaluated the KIT locus, an obvious candidate gene locus affecting variation in blood‐related traits. Using dense single nucleotide polymorphism marker data on SSC 8 and the marker‐assisted association test, the strong association of the KIT locus with blood phenotypes was confirmed. In conclusion, our study identified both previously reported and novel QTL affecting baseline haematological parameters in pigs. Additionally, the positional candidate genes identified here could play an important role in elucidating the genetic architecture of haematological phenotype variation in swine and in humans.     

Multiple restriction fragment length polymorphisms in the porcine calcium release channel gene (CRC): assignment to the halothane (HAL) linkage group

Two cDNA probes for the porcine calcium release channel gene (CRC) were used in restriction fragment length polymorphism (RFLP) analysis in an attempt to develop genetic markers linked to the malignant hyperthermia (stress susceptibility) gene (HAL). Three TaqI RFLPs, denoted CRC1-CRC3, each composed of two alleles, were detected. RFLPs were also detected with MspI and PvuII, but the MspI RFLP correlated completely with CRC3 in this material and the PvuII RFLP could not be scored reliably due to a minute size difference between the two allelic fragments. The autosomal codominant inheritance of these RFLP loci was confirmed by family analyses. Significant evidence for genetic linkage between the CRC1/CRC3 loci and the A1BG locus in the HAL linkage group confirmed a previous assignment of the CRC gene to chromosome 6 in the pig.     

Molecular-Marker-Facilitated Investigations of Quantitative-Trait Loci in Maize. I. Numbers, Genomic Distribution and Types of Gene Action

Individual genetic factors which underlie variation in quantitative traits of maize were investigated in each of two F2 populations by examining the mean trait expressions of genotypic classes at each of 17-20 segregating marker loci. It was demonstrated that the trait expression of marker locus classes could be interpreted in terms of genetic behavior at linked quantitative trait loci (QTLs). For each of 82 traits evaluated, QTLs were detected and located to genomic sites. The numbers of detected factors varied according to trait, with the average trait significantly influenced by almost two-thirds of the marked genomic sites. Most of the detected associations between marker loci and quantitative traits were highly significant, and could have been detected with fewer than the 1800-1900 plants evaluated in each population. The cumulative, simple effects of marker-linked regions of the genome explained between 8 and 40% of the phenotypic variation for a subset of 25 traits evaluated. Single marker loci accounted for between 0.3% and 16% of the phenotypic variation of traits. Individual plant heterozygosity, as measured by marker loci, was significantly associated with variation in many traits. The apparent types of gene action at the QTLs varied both among traits and between loci for given traits, although overdominance appeared frequently, especially for yield-related traits. The prevalence of apparent overdominance may reflect the effects of multiple QTLs within individual marker-linked regions, a situation which would tend to result in overestimation of dominance. Digenic epistasis did not appear to be important in determining the expression of the quantitative traits evaluated. Examination of the effects of marked regions on the expression of pairs of traits suggests that genomic regions vary in the direction and magnitudes of their effects on trait correlations, perhaps providing a means of selecting to dissociate some correlated traits. Marker-facilitated investigations appear to provide a powerful means of examining aspects of the genetic control of quantitative traits. Modifications of the methods employed herein will allow examination of the stability of individual gene effects in varying genetic backgrounds and environments.     

A stochastic expectation and maximization algorithm for detecting quantitative trait-associated genes

MOTIVATION: Most biological traits may be correlated with the underlying gene expression patterns that are partially determined by DNA sequence variation. The correlations between gene expressions and quantitative traits are essential for understanding the functions of genes and dissecting gene regulatory networks. RESULTS: In the present study, we adopted a novel statistical method, called the stochastic expectation and maximization (SEM) algorithm, to analyze the associations between gene expression levels and quantitative trait values and identify genetic loci controlling the gene expression variations. In the first step, gene expression levels measured from microarray experiments were assigned to two different clusters based on the strengths of their association with the phenotypes of a quantitative trait under investigation. In the second step, genes associated with the trait were mapped to genetic loci of the genome. Because gene expressions are quantitative, the genetic loci controlling the expression traits are called expression quantitative trait loci. We applied the same SEM algorithm to a real dataset collected from a barley genetic experiment with both quantitative traits and gene expression traits. For the first time, we identified genes associated with eight agronomy traits of barley. These genes were then mapped to seven chromosomes of the barley genome. The SEM algorithm and the result of the barley data analysis are useful to scientists in the areas of bioinformatics and plant breeding. Availability and implementation: The R program for the SEM algorithm can be downloaded from our website: http://www.statgen.ucr.edu.     

Genetic variation in lipoprotein (a) levels in families enriched for coronary artery disease is determined almost entirely by the apolipoprotein (a) gene locus.

Lipoprotein (a) (Lp[a]) is a cholesterol-rich lipoprotein resembling LDL but also containing a large polypeptide designated apolipoprotein (a) (apo[a]). Its levels are highly variable among individuals and, in a number of studies, are strongly correlated with the risk of coronary artery disease (CAD). In an effort to determine which genes control Lp(a) levels, we have studied 25 multiplex families (comprising 298 members) enriched for CAD. The apo(a) gene was genotyped among the families, using a highly informative pulse-field gel electrophoresis procedure. In addition, polymorphisms of the gene for the other major protein of Lp(a), apolipoprotein B (apoB), were examined. Quantitative sib-pair linkage analysis indicates that apo(a) is the major gene controlling Lp(a) levels in this CAD population (P = .001; 99 sib pairs), whereas the apoB gene demonstrated no significant quantitative linkage effect. We estimate that the apo(a) locus accounts for < or = 98% of variance of Lp(a) serum levels. Approximately 43% of this variation is explained by size polymorphisms within the apo(a) gene. These results indicate that the apo(a) gene is the major determinant of Lp(a) serum levels not only in the general population but also in a high-risk CAD population.     

Quantitative trait loci affecting amylose,amylopectin and starch content in maize recombinant inbred lines

The loci explaining the variability of quantitative traits related to starch content and composition (amylose, amylopectin and water soluble fraction) were searched for in maize kernels. Multifactorial genetic methods were used to detect and locate QTLs (quantitative trait loci) on a genetic map consisting mainly of RFLP markers for genes with known function. The genetic material was recombinant inbred lines originating from parents differing in starch structure (dent vs. flint). Kernels were harvested from field grown plants for two successive years and under two pollination systems. Main effect and epistasis QTLs were detected using two methods, composite interval mapping (MQTL) and ANOVA. Despite large year-to-year differences, physiologically meaningful co-locations were observed between trait QTLs. Moreover, the number of expressed sequences on our map allowed the search for co-locations between QTLs and genes involved in carbohydrate metabolism. The main co-location was between an amylose QTL and Shrunken 2 (SH2) locus, on chromosome 3 (SH2 encoding for the large subunit of ADPglucose pyrophosphorylase). The importance of this locus as a candidate gene for a starch QTL is in agreement with previous studies based either on QTL co-locations or on revertant analysis. Other co-locations were observed between amylose and amylopectin QTLs and the two loci of IVR1 invertase genes on chromosomes 2 and 10. Further comparison with previously detected QTLs for carbohydrate metabolism in maize leaves showed consistent co-location in map regions devoid of candidate genes, such as near chromosome 1S telomere. The possible contribution of regulatory genes in this region is discussed.     

Apolipoprotein (apo) E genotypes by polymerase chain reaction and allele-specific oligonucleotide probes: no detectable linkage disequilibrium between apo E and apo CII

Summary Allelic sequence variation in the apolipoprotein (apo) E gene has been analysed by means of synthetic oligonucleotide probes that detect single base pair substitutions in the codons for amino acid positions 112 and 158, substitutions that are responsible for the common isoforms. Use of the polymerase chain reaction procedure to amplify a sequence of 330 base pairs of the human apo E gene has permitted the development of a robust method for apo E genotyping. This technique has been used to determine the apo E genotype in 95 individuals in whom the genotype for an apo CII TaqI restriction fragment length polymorphism has also been determined. No strong linkage disequilibrium between the two gene loci was detected. This suggests that the metabolic effects of variation, in the apo E and apo CII genes, as detected by the polymorphisms used here, would operate in a statistically independent manner.     

Genetic variants and underlying mechanisms influencing variance heterogeneity in maize

Traditional genetic studies focus on identifying genetic variants associated with the mean difference in a quantitative trait. Because genetic variants also influence phenotypic variation via heterogeneity, we conducted a variance‐heterogeneity genome‐wide association study to examine the contribution of variance heterogeneity to oil‐related quantitative traits. We identified 79 unique variance‐controlling single nucleotide polymorphisms (vSNPs) from the sequences of 77 candidate variance‐heterogeneity genes for 21 oil‐related traits using the Levene test (P < 1.0 × 10^?5). About 30% of the candidate genes encode enzymes that work in lipid metabolic pathways, most of which define clear expression variance quantitative trait loci. Of the vSNPs specifically associated with the genetic variance heterogeneity of oil concentration, 89% can be explained by additional linked mean‐effects genetic variants. Furthermore, we demonstrated that gene × gene interactions play important roles in the formation of variance heterogeneity for fatty acid compositional traits. The interaction pattern was validated for one gene pair (GRMZM2G035341 and GRMZM2G152328) using yeast two‐hybrid and bimolecular fluorescent complementation analyses. Our findings have implications for uncovering the genetic basis of hidden additive genetic effects and epistatic interaction effects, and we indicate opportunities to stabilize efficient breeding and selection of high‐oil maize (Zea mays L.).     

Functional organization of woody plant assemblages along precipitation and human disturbance gradients in a seasonally dry tropical forest

Chronic anthropogenic disturbances (CAD) and rainfall are important drivers of plant community assembly, but little is known about the role played by inter‐ and intraspecific trait variation as communities respond to these pervasive forces. Here, we examined the hypothesis that lower precipitation and higher CAD reduce both intra‐ and interspecific trait variation in Caatinga dry forests. We sampled woody plants across 15 plots along precipitation and CAD gradients and measured resource‐use traits. The effects of precipitation and CAD on RaoQ functional diversity were decomposed into species turnover and intraspecific variability. We used “T‐statistics” to assess the trait sorting from the regional pool to local communities (i.e., external filtering), and within‐community forces leading to low trait overlap (i.e., internal filtering) at individual and species levels. Intraspecific variability explained at least one‐third of the total trait variation and 46% of variation in multitrait diversity across communities. Increasing disturbance reduced multitrait diversity, while precipitation affected some particular traits, such as wood density. Overall, precipitation determined species sorting across communities, while disturbance relaxed internal filters, leading to higher trait overlap within communities due to higher intraspecific variability. Our results suggest that the woody Caatinga flora contains a substantial amount of both inter‐ and intraspecific trait variation. This variation is not randomly distributed within and across communities, but varies according to rainfall conditions and disturbance intensity. These findings reinforce the emerging idea that human disturbances can reorganize plant communities at multiple scales and highlight trait variability as a key biological asset for the resilience of dry forests.     

Quantitative trait loci in Drosophila

Phenotypic variation for quantitative traits results from the simultaneous segregation of alleles at multiple quantitative trait loci. Understanding the genetic architecture of quantitative traits begins with mapping quantitative trait loci to broad genomic regions and ends with the molecular definition of quantitative trait loci alleles. This has been accomplished for some quantitative trait loci in Drosophila. Drosophila quantitative trait loci have sex-, environment- and genotype-specific effects, and are often associated with molecular polymorphisms in non-coding regions of candidate genes. These observations offer valuable lessons to those seeking to understand quantitative traits in other organisms, including humans.     

Dimension reduction for mapping mRNA abundance as quantitative traits

The advent of sophisticated genomic techniques for gene mapping and microarray analysis has provided opportunities to map mRNA abundance to quantitative trait loci (QTL) throughout the genome. Unfortunately, simple mapping of each individual mRNA trait on the scale of a typical microarray experiment is computationally intensive, subject to high sample variance, and therefore underpowered. However, this problem can be addressed by capitalizing on correlation among the large number of mRNA traits. We present a method to reduce the dimensionality for mapping gene expression data as quantitative traits. We used a blind method, principal components, and a sighted method, hierarchical clustering seeded by disease relevant traits, to define new traits composed of a small collection of promising mRNAs. We validated the principle of our approach by mapping the expression levels of metabolism genes in a population of F(2)-ob/ob mice derived from the BTBR and C57BL/6J strains. We found that lipogenic and gluconeogenic mRNAs, which are known targets of insulin action, were closely associated with the insulin trait. Multiple interval mapping and Bayesian interval mapping of this new trait revealed significant linkages to chromosome regions that were contained in loci associated with type 2 diabetes in this same mouse sample. As a further statistical refinement, we show that principal component analysis also effectively reduced dimensions for mapping phenotypes composed of mRNA abundances.