Quantitative Trait Linkage Analysis Research Articles

Sex-specific differences in the genetic and environmental effects on cardiac phenotypic variation assessed by echocardiography

The drivers of sexual dimorphism in heart failure phenotypes are currently poorly understood. Divergent phenotypes may result from differences in heritability and genetic versus environmental influences on the interplay of cardiac structure and function. To assess sex-specific heritability and genetic versus environmental contributions to variation and inter-relations between echocardiography traits in a large community-based cohort. We studied Framingham Heart Study participants of Offspring Cohort examination 8 (2005–2008) and Third Generation Cohort examination 1 (2002–2005). Five cardiac traits and six functional traits were measured using standardized echocardiography. Sequential Oligogenic Linkage Analysis Routines (SOLAR) software was used to perform singular and bivariate quantitative trait linkage analysis. In our study of 5674 participants (age 49 ± 15 years; 54% women), heritability for all traits was significant for both men and women. There were no significant differences in traits between men and women. Within inter-trait correlations, there were two genetic, and four environmental trait pairs with sex-based differences. Within both significant genetic trait pairs, men had a positive relation, and women had no significant relation. We observed significant sex-based differences in inter-trait genetic and environmental correlations between cardiac structure and function. These findings highlight potential pathways of sex-based divergent heart failure phenotypes.

Network-based quantitative trait linkage analysis of microbiome composition in inflammatory bowel disease families.

Introduction: Inflammatory bowel disease (IBD) is characterized by a dysbiosis of the gut microbiome that results from the interaction of the constituting taxa with one another, and with the host. At the same time, host genetic variation is associated with both IBD risk and microbiome composition. Methods: In the present study, we defined quantitative traits (QTs) from modules identified in microbial co-occurrence networks to measure the inter-individual consistency of microbial abundance and subjected these QTs to a genome-wide quantitative trait locus (QTL) linkage analysis. Results: Four microbial network modules were consistently identified in two cohorts of healthy individuals, but three of the corresponding QTs differed significantly between IBD patients and unaffected individuals. The QTL linkage analysis was performed in a sub-sample of the Kiel IBD family cohort (IBD-KC), an ongoing study of 256 German families comprising 455 IBD patients and 575 first- and second-degree, non-affected relatives. The analysis revealed five chromosomal regions linked to one of three microbial module QTs, namely on chromosomes 3 (spanning 10.79 cM) and 11 (6.69 cM) for the first module, chr9 (0.13 cM) and chr16 (1.20 cM) for the second module, and chr13 (19.98 cM) for the third module. None of these loci have been implicated in a microbial phenotype before. Discussion: Our study illustrates the benefit of combining network and family-based linkage analysis to identify novel genetic drivers of microbiome composition in a specific disease context.

Identification of a Novel Locus for Gait Speed Decline With Aging: The Long Life Family Study.

Gait speed is a powerful indicator of health with aging. Potential genetic contributions to gait speed and its decline with aging are not well defined. We determined the heritability of and potential genetic regions underlying change in gait speed using longitudinal data from 2379 individuals belonging to 509 families in the Long Life Family Study (mean age 64 ± 12, range 30-110 years; 45% men). Gait speed was measured over 4 m at baseline and follow-up (7 ± 1 years). Quantitative trait linkage analyses were completed using pedigree-based maximum likelihood methods with logarithm of the odds (LOD) scores greater than 3.0, indicating genome-wide significance. We also performed linkage analysis in the top 10% of families contributing to LOD scores to allow for heterogeneity among families (HLOD). Data were adjusted for age, sex, height, and field center. At baseline, 26.9% of individuals had "slow" gait speed less than 1.0 m/s (mean: 1.1 ± 0.2 m/s) and gait speed declined at a rate of -0.02 ± 0.03 m/s per year (p < .0001). Baseline and change in gait speed were significantly heritable (h2 = 0.24-0.32, p < .05). We did not find significant evidence for linkage for baseline gait speed; however, we identified a significant locus for change in gait speed on chromosome 16p (LOD = 4.2). A subset of 21 families contributed to this linkage peak (HLOD = 6.83). Association analyses on chromosome 16 showed that the strongest variant resides within the ADCY9 gene. Further analysis of the chromosome 16 region, and ADCY9 gene, may yield new insight on the biology of mobility decline with aging.

Genome-Wide Linkage Analysis Identifies a Novel Locus for Grip Strength: The Long Life Family Study

Grip strength declines with aging, is an indicator of overall health, and predicts mortality among older adults. Herein, we quantified the genetic contributions to grip strength among 4534 individuals, belonging to 574 families in the Long Life Family Study (age 70.3 ± 15.7, range 24–110 years; 56% women). Grip strength was measured using a handheld dynamometer, and the maximum value of two trials in the stronger hand was used. Quantitative trait linkage analysis was completed using pedigree-based maximum-likelihood methods with logarithm of the odds (LOD) scores >3.0 indicating genome-wide significance. Linkage analysis in the top 10% of families contributing to LOD scores was also performed to allow for heterogeneity among families (HLOD). All analyses were adjusted for age, sex, height and field center. Grip strength was lower per one year of older age (β: -0.34 ± 0.01kg, p <0.01), and overall: 24.3% of men and 19.3% of women had “low” grip strength according to European Working Group on Sarcopenia definitions. Grip strength was highly heritable (h2 = 0.37, p<0.05). We identified a potentially novel locus for grip strength on chromosome 18p (LOD 3.18) with 26 families contributing to this linkage peak (HLOD = 10.94). Deep sequencing of the chromosome 18 region may yield fundamental insight on the biology of muscle weakness with aging, and may help identify novel therapeutic targets for treatment and prevention of this common condition.

GENOME-WIDE LINKAGE ANALYSIS IDENTIFIES A NOVEL LOCUS FOR LONGITUDINAL GAIT SPEED CHANGE WITH AGING

Gait speed is an indicator of health and function with aging. The potential genetic contributions to gait speed and its decline with aging are not well characterized. We sought to better quantify the genetic contributions to and identify potential genes and genetic variants underlying change in gait speed among older adults. To accomplish these aims, we used data from 2379 individuals belonging to 509 families in the Long Life Family Study (mean age 64 ± 12, range 30–110 years; 45% men). Gait-speed was measured over 4 meters at baseline and after an average of 7±1.1 years. Quantitative trait linkage analyses were completed using pedigree-based maximum-likelihood methods with logarithm of the odds (LOD) scores > 3.3 indicating genome-wide significance. We also performed linkage analysis in the top 10% of families contributing to LOD scores to allow for heterogeneity among families (HLOD). Data were adjusted for age, sex, height and field center. At baseline, 26.9% of individuals had “low” gait-speed <1.0 m/s (mean: 1.1±0.2 m/s) and gait speed declined at a rate of -0.02±0.03 m/s per year (p<0.0001). Baseline and change in gait-speed were significantly heritable (h2 = 0.24-0.32, p<0.05). We did not find significant evidence for linkage for baseline gait speed; however, we identified a potentially novel locus for change in gait speed on chromosome 16p (LOD 4.2). A subset of 21 families contributed to this linkage peak (HLOD = 6.83). Sequence analysis of the chromosome 16 region may yield new insight on the biology of age-related mobility decline.

Genome-wide QTL analysis for anxiety trait in bipolar disorder type I

BackgroundGenetic studies have been consistent that bipolar disorder type I (BPI) runs in families and that this familial aggregation is strongly influenced by genes. In a preliminary study, we proved that anxiety trait meets endophenotype criteria for BPI. MethodsWe assessed 619 individuals from the Central Valley of Costa Rica (CVCR) who have received evaluation for anxiety following the same methodological procedure used for the initial pilot study. Our goal was to conduct a multipoint quantitative trait linkage analysis to identify quantitative trait loci (QTLs) related to anxiety trait in subjects with BPI. We conducted the statistical analyses using Quantitative Trait Loci method (Variance-components models), implemented in Sequential Oligogenic Linkage Analysis Routines (SOLAR), using 5606 single nucleotide polymorphism (SNPs). ResultsWe identified a suggestive linkage signal with a LOD score of 2.01 at chromosome 2 (2q13-q14). LimitationsSince confounding factors such as substance abuse, medical illness and medication history were not assessed in our study, these conclusions should be taken as preliminary. ConclusionsWe conclude that region 2q13-q14 may harbor a candidate gene(s) with an important role in the pathophysiology of BPI and anxiety.

Model-Free Linkage Analysis of a Quantitative Trait.

Model-free methods of linkage analysis for quantitative traits are a class of easily implemented, computationally efficient and statistically robust approaches to searching for linkage to a quantitative trait. By "model-free" we refer to methods of linkage analysis that do not fully specify a genetic model (i.e., the causal allele frequency, and penetrance functions). In this chapter we briefly survey the methods that are available, and then we discuss the necessary steps to implement an analysis using the programs GENIBD, SIBPAL and RELPAL in the S.A.G.E. (Statistical Analysis for Genetic Epidemiology) software suite.

Id3 and Id2 Act as a Dual Safety Mechanism in Regulating the Development and Population Size of Innate-like γδ T Cells

The innate-like T cells expressing Vγ1.1 and Vδ6.3 represent a unique T cell lineage sharing features with both the γδ T and the invariant NKT cells. The population size of Vγ1.1(+)Vδ6.3(+) T cells is tightly controlled and usually contributes to a very small proportion of thymic output, but the underlying mechanism remains enigmatic. Deletion of Id3, an inhibitor of E protein transcription factors, can induce an expansion of the Vγ1.1(+)Vδ6.3(+) T cell population. This phenotype is much stronger on the C57BL/6 background than on the 129/sv background. Using quantitative trait linkage analysis, we identified Id2, a homolog of Id3, to be the major modifier of Id3 in limiting Vγ1.1(+)Vδ6.3(+) T cell expansion. The Vγ1.1(+)Vδ6.3(+) phenotype is attributed to an intrinsic weakness of Id2 transcription from Id2 C57BL/6 allele, leading to an overall reduced dosage of Id proteins. However, complete removal of both Id2 and Id3 genes in developing T cells suppressed the expansion of Vγ1.1(+)Vδ6.3(+) T cells because of decreased proliferation and increased cell death. We showed that conditional knockout of Id2 alone is sufficient to promote a moderate expansion of γδ T cells. These regulatory effects of Id2 and Id3 on Vγ1.1(+)Vδ6.3(+) T cells are mediated by titration of E protein activity, because removing one or more copies of E protein genes can restore Vγ1.1(+)Vδ6.3(+) T cell expansion in Id2 and Id3 double conditional knockout mice. Our data indicated that Id2 and Id3 collaboratively control survival and expansion of the γδ lineage through modulating a proper threshold of E proteins.

Abstract P153: Genetic Linkage and Association of Echocardiographic Measures in the Fels Longitudinal Study

Measures of cardiac structure such as left ventricular mass (LVM) have been shown to be significantly heritable. Relative to other complex traits, however, gene variants influencing echocardiographic traits have been less frequently identified. In this study of subjects from the Fels Longitudinal Study, our aim was to perform quantitative trait linkage and genome-wide association (GWA) analyses on LVM, relative wall thickness (RWT), fractional shortening (FS), aortic root diameter (ARD), and LVM index (LVMI; LVM/height 2.7 ). The study sample consisted of 1,060 (467 male, 593 female) whites aged 8-97 years from 131 families. Variables were inverse normal transformed for all analyses. Each subject was genotyped with the Illumina Human 610-Quad BeadChip containing more than 550,000 single nucleotide polymorphism (SNP) markers. Variance-component linkage analyses were conducted using a subset of 17,561 genome-wide SNP markers in genetic equilibrium with each other. GWA analyses were conducted using all SNPs and the measured genotype method implemented in SOLAR, allowing for residual non-independence among relatives After adjusting for covariates of age, sex, BMI, and population stratification, all echocardiograpic traits were significantly heritable (p &lt; 0.00006); h 2 (SE) for LVM, LVMI, RWT, FS, and ARD were 0.28 (0.07), 0.36 (0.07), 0.22 (0.07), 0.27 (0.06), and 0.55 (0.06), respectively. Linkage analyses revealed significant linkage of LVMI to chromosome 1p31 (LOD=3.64 at 96cM) in a region where the LEPR (leptin receptor), PDE4B (phosphodiesterase 4B, cAMP-specific), NEGR1 (neuronal growth regulator 1), and TNNI3K (TNNI3 interacting kinase) genes are located. For ARD, we identified chromosomal region 13q14 (LOD = 3.88 at 45cM) which harbors the FOXO1 (forkhead box O1) and TSC22D1 (TSC22 domain family, member 1) genes. Suggestive (LOD &gt; 2.0) linkages were found on chromosomes 1, 2, 3, 4, 9 and 19 for the various traits. In GWA analyses, significant ( χ 2 &gt;27.85) association was found between LVMI and SNP rs7939215 on chromosome 11p15. For LVM we observed evidence of a suggestive association ( χ 2 &gt;22.70) with rs660464 in the NRG3 (neuregulin 3) gene, which has been associated with hypertrophy among the Amish. Other suggestive associations were found between FS and SNPs rs12485048 and rs5753622 on chromosome 22q12, and SNP rs2993639 chromosome on 3q21. In summary, we identified several significant linkage and association signals for cardiac measures. Future work will include replicating these results in other study populations.

A non-human primate system for large-scale genetic studies of complex traits.

Non-human primates provide genetic model systems biologically intermediate between humans and other mammalian model organisms. Populations of Caribbean vervet monkeys (Chlorocebus aethiops sabaeus) are genetically homogeneous and large enough to permit well-powered genetic mapping studies of quantitative traits relevant to human health, including expression quantitative trait loci (eQTL). Previous transcriptome-wide investigation in an extended vervet pedigree identified 29 heritable transcripts for which levels of expression in peripheral blood correlate strongly with expression levels in the brain. Quantitative trait linkage analysis using 261 microsatellite markers identified significant (n = 8) and suggestive (n = 4) linkages for 12 of these transcripts, including both cis- and trans-eQTL. Seven transcripts, located on different chromosomes, showed maximum linkage to markers in a single region of vervet chromosome 9; this observation suggests the possibility of a master trans-regulator locus in this region. For one cis-eQTL (at B3GALTL, beta-1,3-glucosyltransferase), we conducted follow-up single nucleotide polymorphism genotyping and fine-scale association analysis in a sample of unrelated Caribbean vervets, localizing this eQTL to a region of <200 kb. These results suggest the value of pedigree and population samples of the Caribbean vervet for linkage and association mapping studies of quantitative traits. The imminent whole genome sequencing of many of these vervet samples will enhance the power of such investigations by providing a comprehensive catalog of genetic variation.

Neuropsychological intra‐individual variability explains unique genetic variance of ADHD and shows suggestive linkage to chromosomes 12, 13, and 17

Attention-deficit/hyperactivity disorder (ADHD) is a highly heritable neuropsychiatric disorder that is usually accompanied by neuropsychological impairments. The use of heritable, psychometrically robust traits that show association with the disorder of interest can increase the power of gene-finding studies. Due to the robust association of intra-individual variability with ADHD on a phenotypic and genetic level, intra-individual variability is a prime candidate for such an attempt. We aimed to combine intra-individual variability measures across tasks into one more heritable measure, to examine the relatedness to other cognitive factors, and to explore the genetic underpinnings through quantitative trait linkage analysis. Intra-individual variability measures from seven tasks were available for 238 ADHD families (350 ADHD-affected and 195 non-affected children) and 147 control families (271 children). Intra-individual variability measures from seven different tasks shared common variance and could be used to construct an aggregated measure. This aggregated measure was largely independent from other cognitive factors related to ADHD and showed suggestive linkage to chromosomes 12q24.3 (LOD = 2.93), 13q22.2 (LOD = 2.36), and 17p13.3 (LOD = 2.00). A common intra-individual variability construct can be extracted from very diverse neuropsychological tasks; this construct taps into unique genetic aspects of ADHD and may relate to loci conferring risk for ADHD (12q24.3 and 17p13.3) and possibly autism (12q24.3). Given that joining of data across sites boosts the power for genetic analyses, our findings are promising in showing that intra-individual variability measures are viable candidates for across site analyses where different tasks have been used.

GADS software for parametric linkage analysis of quantitative traits distributed as a point-mass mixture

Often the quantitative data coming from proteomics and metabolomics studies have irregular distribution with a spike. None of the wide used methods for human QTL mapping are applicable to such traits. Researchers have to reduce the sample, excluding the spike, and analyze only continuous measurements. In this study, we propose a method for the parametric linkage analysis of traits with a spike in the distribution, and a software GADS, which implements this method. Our software includes not only the programs for parametric linkage analysis, but also the program for complex segregation analysis, which allows the estimation of the model parameters used in linkage. We tested our method on the real data about vertical cup-to-disc ratio, the important characteristic of the optic disc associated with glaucoma, in a large pedigree from a Dutch isolated population. Significant linkage signal was identified on chromosome 6 with the help of GADS, whereas the analysis of the normal distributed part of the sample demonstrated only a suggestive linkage peak on this chromosome.The software GADS is freely available at http://mga.bionet.nsc.ru/soft/index.html.

Genetic analysis of serum osteocalcin and bone mineral in multigenerational Afro-Caribbean families

Osteocalcin is a major component of bone matrix. Concentrations of total, carboxylated, and uncarboxylated osteocalcin, are highly heritable and genetically correlated with bone mineral content (BMC) within African ancestry families. Osteocalcin (OC) is a protein constituent of bone matrix and a marker of bone formation. We characterized the heritability of serum OC measures and identified genomic regions potentially involved in the regulation of OC via high-density genome-wide linkage analysis in African ancestry individuals. African ancestry individuals (n = 459) were recruited, without regard to health status, from seven probands (mean family size = 66; 4,373 relative pairs). Residual heritability of serum OC measures was estimated and multipoint quantitative trait linkage analysis was performed using pedigree-based maximum likelihood methods. Residual heritabilities of total OC, uncarboxylated OC, carboxylated OC and percent uncarboxylated OC were 0.74 ± 0.10, 0.89 ± 0.08, 0.46 ± 0.10 and 0.41 ± 0.09, respectively. All OC measures were genetically correlated with whole body BMC. We obtained strong evidence of bivariate linkage for percent uncarboxylated OC and whole body BMC on chromosome 17 (logarithm of the odds [LOD] = 3.15, 99 cM). All forms of OC were highly heritable and genetically correlated with total body BMC in these African ancestry families. The identified linkage region contains several candidate genes for bone and energy metabolism including COL1A1 and TNFRSF11A. Further studies of this genomic region may reveal novel insight into the genetic regulation of OC and bone mineralization.

Detecting Pleiotropy and Epistasis Using Variance Components Linkage Analysis in jPAP

jPAP (Java Pedigree Analysis Package) performs variance components linkage analysis of either quantitative or discrete traits. Multivariate linkage analysis of two or more traits (all quantitative, all discrete, or any combination) allows the inference of pleiotropy between the traits. The inclusion of multiple quantitative trait loci in linkage analysis allows the inference of epistasis between loci. A user-friendly graphical user interface facilitates the usage of jPAP.

Human Plasma Glycome in Attention-Deficit Hyperactivity Disorder and Autism Spectrum Disorders

Over a half of all proteins are glycosylated, and their proper glycosylation is essential for normal function. Unfortunately, because of structural complexity of nonlinear branched glycans and the absence of genetic template for their synthesis, the knowledge about glycans is lagging significantly behind the knowledge about proteins or DNA. Using a recently developed quantitative high throughput glycan analysis method we quantified components of the plasma N-glycome in 99 children with attention-deficit hyperactivity disorder (ADHD), 81 child and 5 adults with autism spectrum disorder, and a total of 340 matching healthy controls. No changes in plasma glycome were found to associate with autism spectrum disorder, but several highly significant associations were observed with ADHD. Further structural analysis of plasma glycans revealed that ADHD is associated with increased antennary fucosylation of biantennary glycans and decreased levels of some complex glycans with three or four antennas. The design of this study prevented any functional conclusions about the observed associations, but specific differences in glycosylation appears to be strongly associated with ADHD and warrants further studies in this direction.

The Maximum-Likelihood-Binomial method revisited: a robust approach for model-free linkage analysis of quantitative traits in large sibships

Model-free linkage analysis methods, based on identity-by-descent allele sharing, are commonly used for complex trait analysis. The Maximum-Likelihood-Binomial (MLB) approach, which is based on the hypothesis that parental alleles are binomially distributed among affected sibs, is particularly popular. An extension of this method to quantitative traits (QT) has been proposed (MLB-QTL), based on the introduction of a latent binary variable capturing information about the linkage between the QT and the marker. Interestingly, the MLB-QTL method does not require the decomposition of sibships into constituent sibpairs and requires no prior assumption about the distribution of the QT. We propose a new formulation of the MLB method for quantitative traits (nMLB-QTL) that explicitly takes advantage of the independence of paternal and maternal allele transmission under the null hypothesis of no linkage. Simulation studies under H₀ showed that the nMLB-QTL method generated very consistent type I errors. Furthermore, simulations under the alternative hypothesis showed that the nMLB-QTL method was slightly, but systematically more powerful than the MLB-QTL method, whatever the genetic model, residual correlation, ascertainment strategy and sibship size considered. Finally, the power of the nMLB-QTL method is illustrated by a chromosome-wide linkage scan for a quantitative endophenotype of leprosy infection. Overall, the nMLB-QTL method is a robust, powerful, and flexible approach for detecting linkage with quantitative phenotypes, particularly in studies of non Gaussian phenotypes in large sibships.

An Alternative Model for Quantitative Trait Loci (QTL) Analysis in General Pedigrees

Linkage detection of a trait involves detecting regions of the genome that influence the trait. A wide variety of statistical models are currently employed for linkage analysis of quantitative traits. Many of these models are developed under some assumptions of the trait distributions. Violation of the assumptions about the trait generally affects the type I error and power for linkage detection. In this paper, we have proposed a trait-model-free approach for linkage analysis of a quantitative trait in general pedigrees. The conditional segregation of marker alleles given the trait is modeled using a latent-variable logistic model. A likelihood-ratio test is used to test for linkage under our model. The main applicability of this approach lies in the fact that it always provides correct type I error no matter what the trait distribution is and thus can be used for nonnormal traits or for selected samples. By means of simulation studies, we have compared the power of our proposed model with existing approaches for nonnormal traits. The performance of these methods was also studied on a real dataset. We have demonstrated the usefulness of our approach in terms of power and robustness for linkage detection of quantitative traits in general pedigrees.

Genomewide Linkage and Peakwide Association Analyses of Carotid Plaque in Caribbean Hispanics

Atherosclerosis is a complex subclinical cardiovascular disorder with a substantial genetic component. This study sought to identify genetic loci influencing carotid plaque in 2 independent samples. B-mode ultrasound was performed to determine the presence and area of carotid plaque. Variance components analysis was used to test for linkage using 383 autosomal microsatellite markers in 1308 subjects from 100 Dominican families. Multiple linear and logistic regression models were used to investigate the association between plaque traits and 18,904 single nucleotide polymorphisms under the 1-logarithm of odds unit down regions of linkage peaks in an independent community-based data set (N = 941, 41% Dominicans) from the Northern Manhattan Study. After adjustment for age, hypertension, diabetes mellitus, cigarette pack-years, body mass index, and waist-to-hip ratio, significant heritability was detected for plaque presence (h² = 0.50 ± 0.14, P < 0.0001) and plaque area (h²=0.17 ± 0.04, P < 0.0001). Quantitative and dichotomous trait linkage analyses obtained similar results and identified 4 regions with multipoint logarithm of odds scores ≥ 2.00 on 7q36, 11p15, 14q32, and 15q23. In the association analysis of the 4 linkage peaks, several single nucleotide polymorphisms in or near SOX6, FSD2, AP3S2, EFTUD1, and MYOD1 were associated with carotid plaque traits with a nominal P ≤ 0.0005 in the Northern Manhattan Study data set and with a P ≤ 0.01 in Northern Manhattan Study Dominican subset. Carotid plaque has considerable heritability and may be influenced by loci on chromosomes 11p15, 14q32, and 15q23. The SOX6 gene within the bone morphogenic protein pathway could be a candidate for carotid plaque. Larger independent studies are needed to validate these findings.

Localization of genes for V+LDL plasma cholesterol levels on two diets in the opossum Monodelphis domestica

Plasma cholesterol levels among individuals vary considerably in response to diet. However, the genes that influence this response are largely unknown. Non-HDL (V+LDL) cholesterol levels vary dramatically among gray, short-tailed opossums fed an atherogenic diet, and we previously reported that two quantitative trait loci (QTLs) influenced V+LDL cholesterol on two diets. We used hypothesis-free, genome-wide linkage analyses on data from 325 pedigreed opossums and located one QTL for V+LDL cholesterol on the basal diet on opossum chromosome 1q [logarithm of the odds (LOD) = 3.11, genomic P = 0.019] and another QTL for V+LDL on the atherogenic diet (i.e., high levels of cholesterol and fat) on chromosome 8 (LOD = 9.88, genomic P = 5 x 10(-9)). We then employed a novel strategy involving combined analyses of genomic resources, expression analysis, sequencing, and genotyping to identify candidate genes for the chromosome 8 QTL. A polymorphism in ABCB4 was strongly associated (P = 9 x 10(-14)) with the plasma V+LDL cholesterol concentrations on the high-cholesterol, high-fat diet. The results of this study indicate that genetic variation in ABCB4, or closely linked genes, is responsible for the dramatic differences among opossums in their V+LDL cholesterol response to an atherogenic diet.

MQScore_SNP Software for Multipoint Parametric Linkage Analysis of Quantitative Traits in Large Pedigrees

We describe software for multipoint parametric linkage analysis of quantitative traits using information about SNP genotypes. A mixed model of major gene and polygene inheritance is implemented in this software. Implementation of several algorithms to avoid computational underflow and decrease running time permits application of our software to the analysis of very large pedigrees collected in human genetically isolated populations. We tested our software by performing linkage analysis of adult height in a large pedigree from a Dutch isolated population. Three significant and four suggestive loci were identified with the help of our programs, whereas variance-component-based linkage analysis, which requires the pedigree fragmentation, demonstrated only three suggestive peaks. The software package MQScore_SNP is available at http://mga.bionet.nsc.ru/soft/index.html.