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Nengjun Yi

Publications and source records attributed to Nengjun Yi.

At least 19 recordsLinked to original sources
PubMed2006

Bayesian analyses of multiple epistatic QTL models for body weight and body composition in mice.

To comprehensively investigate the genetic architecture of growth and obesity, we performed Bayesian analyses of multiple epistatic quantitative trait locus (QTL) models for body weights at five ages (12 days, 3, 6, 9 and 12 weeks) and body composition traits (weights of two fat pads and five organs) in mice produced from a cross of the F1 between M16i (selected for rapid growth rate) and CAST/Ei (wild-derived strain of small and lean mice) back to M16i. Bayesian model selection revealed a temporally regulated network of multiple QTL for body weight, involving both strong main effects and epistatic effects. No QTL had strong support for both early and late growth, although overlapping combinations of main and epistatic effects were observed at adjacent ages. Most main effects and epistatic interactions had an opposite effect on early and late growth. The contribution of epistasis was more pronounced for body weights at older ages. Body composition traits were also influenced by an interacting network of multiple QTLs. Several main and epistatic effects were shared by the body composition and body weight traits, suggesting that pleiotropy plays an important role in growth and obesity.

Animals↗
PubMed2005

Accelerated development of arthritis in mice lacking endothelial selectins.

The selectins, along with very late antigen-4 and CD44, have been implicated in mediating leukocyte rolling interactions that lead to joint recruitment and inflammation during the pathogenesis of rheumatoid arthritis. Previously, we showed that P-selectin deficiency in mice resulted in accelerated onset of joint inflammation in the murine collagen-immunized arthritis model. Here, we report that mice deficient either in E-selectin or in E-selectin and P-selectin (E/P-selectin mutant) also exhibit accelerated development of arthritis compared with wild type mice in the CIA model, suggesting that these adhesion molecules perform overlapping functions in regulating joint disease. Analyses of cytokine and chemokine expression in joint tissue from E/P-selectin mutant mice before the onset of joint swelling revealed significantly higher joint levels of macrophage inflammatory protein-1alpha and IL-1beta compared to wild-type mice. IL-1beta remained significantly increased in E/P-selectin mutant joint tissue during the early and chronic phases of arthritis. Overall, these data illustrate the novel finding that E-selectin and P-selectin expression can significantly influence cytokine and chemokine production in joint tissue, and suggest that these adhesion molecules play important regulatory roles in the development of arthritis in E/P-selectin mutant mice.

Animals↗
PubMed2005

Bayesian model selection for genome-wide epistatic quantitative trait loci analysis.

The problem of identifying complex epistatic quantitative trait loci (QTL) across the entire genome continues to be a formidable challenge for geneticists. The complexity of genome-wide epistatic analysis results mainly from the number of QTL being unknown and the number of possible epistatic effects being huge. In this article, we use a composite model space approach to develop a Bayesian model selection framework for identifying epistatic QTL for complex traits in experimental crosses from two inbred lines. By placing a liberal constraint on the upper bound of the number of detectable QTL we restrict attention to models of fixed dimension, greatly simplifying calculations. Indicators specify which main and epistatic effects of putative QTL are included. We detail how to use prior knowledge to bound the number of detectable QTL and to specify prior distributions for indicators of genetic effects. We develop a computationally efficient Markov chain Monte Carlo (MCMC) algorithm using the Gibbs sampler and Metropolis-Hastings algorithm to explore the posterior distribution. We illustrate the proposed method by detecting new epistatic QTL for obesity in a backcross of CAST/Ei mice onto M16i.

Algorithms↗
PubMed2005

Genetic analysis of the antibody response to AAV2 and factor IX.

We have analyzed the antibody response against either AAV2 or canine F.IX (cF.IX) in parental C57BL/6 (B6) and DBA/2 (D2) and 18 strains of B6 x D2 (BXD) recombinant inbred (RI) strains of mice after iv administration of AAV2-(ApoE)4/hAAT-cF.IX. There was a higher anti-AAV2 capsid response in B6 compared to D2 mice, with IgG2b being the major isotype separating the high and low responders in these two strains. In contrast, the antibody response to cF.IX was lower than the response to the AAV2 capsid and was limited to the IgG1 isotype in both strains. Genetic linkage analysis of the IgG2b anti-AAV2 antibody response in BXD RI strains revealed a significant locus at D4Mit164 (29 cM, LRS=15.3) and two suggestive loci at D6Mit16 (30.5 cM, LRS=11.2) and D17Mit187 (47.4 cM, LRS=13.1). Genetic linkage analysis of the IgG1 anti-cF.IX antibody response revealed a suggestive locus at D1Mit218 (67 cM, LRS=14.1). Significant epistatic interaction was found between two loci (D8Mit45 and D16Mit47; LOD=6.54) for anti-AAV2 and two other loci (D5Mit348 and D15Mit161; LOD=7.66) for anti-cF.IX. These results indicate that multiple genetic loci independently regulate the isotype-specific antibody response to the AAV2 capsid and the cF.IX transgene.

Alleles↗
PubMed2005

Mapping quantitative trait loci affecting variation in Drosophila triacylglycerol storage.

OBJECTIVE: Recent genetic studies indicate that Drosophila melanogaster could be a powerful model to identify genes involved in mammalian adipocyte differentiation and fat storage. The objective of our study was to identify quantitative trait loci (QTLs) that contribute to variation in triacylglycerol (TAG) storage in two D. melanogaster laboratory strains. RESEARCH METHODS AND PROCEDURES: We used two genetic mapping procedures to identify loci with main and epistatic effects on TAG storage. First, using 68 recombinant inbred lines derived from the unrelated Oregon R and Russian 2b strains, we mapped the location of QTLs affecting TAG storage using both composite interval mapping and Bayesian epistatic methods. Second, we used the quantitative deficiency mapping procedure to identify candidate genes affecting this trait within one of the QTLs identified on the second chromosome. For both mapping experiments, flies were cultured in standard conditions. TAG content of 4- to 5-day-old flies, adjusted for live body mass and total proteins, was used as the phenotypic measure. RESULTS: Multiple QTLs associated with variation in TAG storage were identified by the genome-wide recombination mapping method, and some of them were sex-specific. The QTLs had main effects, but a male-specific epistatic interaction between two QTLs was also found. Finally, two closely linked QTLs were detected by deficiency mapping at 57E1-57E3 and 57E4-57F1 on chromosome 2, the first of which causes female-specific variation in TAG between the Oregon R and 2b strains. DISCUSSION: Our results suggest that variation in TAG storage in D. melanogaster is controlled by different genetic mechanisms and different sets of QTLs in male and female flies.

Adipogenesis↗
PubMed2005

Intentional weight loss reduces mortality rate in a rodent model of dietary obesity.

OBJECTIVE: We used a rodent model of dietary obesity to evaluate effects of caloric restriction-induced weight loss on mortality rate. Research Measures and Procedures: In a randomized parallel-groups design, 312 outbred Sprague-Dawley rats (one-half males) were assigned at age 10 weeks to one of three diets: low fat (LF; 18.7% calories as fat) with caloric intake adjusted to maintain body weight 10% below that for ad libitum (AL)-fed rat food, high fat (HF; 45% calories as fat) fed at the same level, or HF fed AL. At age 46 weeks, the lightest one-third of the AL group was discarded to ensure a more obese group; the remaining animals were randomly assigned to one of three diets: HF-AL, HF with energy restricted to produce body weights of animals restricted on the HF diet throughout life, or LF with energy restricted to produce the body weights of animals restricted on the LF diet throughout life. Life span, body weight, and leptin levels were measured. RESULTS: Animals restricted throughout life lived the longest (p < 0.001). Life span was not different among animals that had been obese and then lost weight and animals that had been nonobese throughout life (p = 0.18). Animals that were obese and lost weight lived substantially longer than animals that remained obese throughout life (p = 0.002). Diet composition had no effect on life span (p = 0.52). DISCUSSION: Weight loss after the onset of obesity during adulthood leads to a substantial increase in longevity in rats.

Aging↗
PubMed2005

Identification of QTL for production traits in chickens.

If the poultry industry hopes to continue to flourish, the identification of potential quantitative trait loci (QTL) for production-related traits must be pursued This remains true despite the sequencing of the chicken genome. In view of this need, a scan of the chicken genome using 72 microsatellite markers was carried out on a meat-type x egg-type resource population measured for production and egg quality traits. Using a Bayesian analysis, potential QTL for a number of traits were identified on several chromosomes. Evidence of eight QTL regions associated with a total of eight traits (specific gravity, albumin height, Haugh score, shell shape, total number of eggs, final body weight, gain, and feed efficiency) was found. Two of these regions, one spanning the area of 263/287 cM on GAA01 and the other spanning the area of 23/28 cM on GAA02, were associated with multiple QTL.

Animals↗
PubMed2004

Epistatic interaction between two nonstructural loci on chromosomes 7 and 3 influences hepatic lipase activity in BSB mice.

BSB mice exhibit a wide range of obesity despite being produced by a backcross of lean C57BL/6J (B) x lean Mus spretus (SPRET/Pt) F1 animals x B. Previous linkage studies identified a quantitative trait locus (QTL) on mouse chromosome 7 with coincident peaks for hepatic lipase activity, obesity, and plasma cholesterol. However, these mice were not analyzed for gene x gene epistasis. Hepatic lipase activity is correlated with obesity and plasma cholesterol levels. In this study, we identified QTLs for plasma hepatic lipase activity with three statistical mapping methods: maximum likelihood interval mapping, Bayesian nonepistatic mapping, and Bayesian epistatic mapping. Bayesian epistatic mapping detected not only the QTL on chromosome 7 but also an additional QTL on chromosome 3, which has a weak main effect but a strong interaction with chromosome 7. SPRET/Pt alleles of the QTL on each chromosome promote hepatic lipase activity. The proportion of phenotypic variance explained by the epistatic effect is higher than that explained by the main effect of the QTL on chromosome 7.

Alleles↗
PubMed2004

Mapping multiple quantitative trait Loci for ordinal traits.

Many complex traits in humans and other organisms show ordinal phenotypic variation but do not follow a simple Mendelian pattern of inheritance. These ordinal traits are presumably determined by many factors, including genetic and environmental components. Several statistical approaches to mapping quantitative trait loci (QTL) for such traits have been developed based on a single-QTL model. However, statistical methods for mapping multiple QTL are not well studied as continuous traits. In this paper, we propose a Bayesian method implemented via the Markov chain Monte Carlo (MCMC) algorithm to map multiple QTL for ordinal traits in experimental crosses. We model the ordinal traits under the multiple threshold model, which assumes a latent continuous variable underlying the ordinal phenotypes. The ordinal phenotype and the latent continuous variable are linked through some fixed but unknown thresholds. We adopt a standardized threshold model, which has several attractive features. An efficient sampling scheme is developed to jointly generate the threshold values and the values of latent variable. With the simulated latent variable, the posterior distributions of other unknowns, for example, the number, locations, genetic effects, and genotypes of QTL, can be computed using existing algorithms for normally distributed traits. To this end, we provide a unified approach to mapping multiple QTL for continuous, binary, and ordinal traits. Utility and flexibility of the method are demonstrated using simulated data.

Algorithms↗
PubMed2004

Reciprocal hemizygosity analysis of mouse hepatic lipase reveals influence on obesity.

OBJECTIVES: We previously demonstrated coincident quantitative trait loci (QTLs) for percentage body fat, plasma hepatic lipase (HL) activity, and plasma cholesterol on mouse chromosome 7. In the present study, we investigated whether hepatic lipase (Lipc) is an obesity gene, whether Lipc interacts with an unknown gene on chromosome 7, and how HL activity is linked to the chromosome 7 locus. RESEARCH METHODS AND PROCEDURES: BSB mice are a model of complex obesity due to interactions among genes from C57BL/6J and Mus spretus (SPRET) in (C57BL/6J x SPRET) x C57BL/6J backcross mice. Five crosses tested the impact on obesity of combinations of inactive (knockout) and wild-type Lipc alleles from C57BL/6J or SPRET in a reciprocal hemizygosity analysis. RESULTS: The combined data from this allelic series suggest that Lipc alleles, and not alleles from a gene linked to Lipc, influence obesity. No interaction between Lipc and chromosome 7 was demonstrated. We confirmed the chromosome 7 QTLs for obesity, HL activity, and cholesterol. Because obesity and HL activity are not consistently associated in the BSB model, linkage of HL activity to chromosome 7 is not secondary to obesity per se. We also report, for the first time to our knowledge, a QTL in mammals for food intake. DISCUSSION: This use of reciprocal hemizygosity analysis in mammals, which, to our knowledge, is the first reported, reveals its power to detect previously unknown effects of Lipc on obesity.

Alleles↗
PubMed2004

A unified Markov chain Monte Carlo framework for mapping multiple quantitative trait loci.

In this article, a unified Markov chain Monte Carlo (MCMC) framework is proposed to identify multiple quantitative trait loci (QTL) for complex traits in experimental designs, based on a composite space representation of the problem that has fixed dimension. The proposed unified approach includes the existing Bayesian QTL mapping methods using reversible jump MCMC algorithm as special cases. We also show that a variety of Bayesian variable selection methods using Gibbs sampling can be applied to the composite model space for mapping multiple QTL. The unified framework not only results in some new algorithms, but also gives useful insight into some of the important factors governing the performance of Gibbs sampling and reversible jump for mapping multiple QTL. Finally, we develop strategies to improve the performance of MCMC algorithms.

Chromosome Mapping↗
PubMed2004

Characterization of epistasis influencing complex spontaneous obesity in the BSB model.

There is growing awareness that complex interactions among multiple genes and environmental factors play an important role in controlling obesity traits. The BSB mouse, which is produced by the backcross of (lean C57BL/6J x lean Mus spretus) x C57BL/6J, provides an excellent model of epistatic obesity. To evaluate potential epistatic interactions among six chromosomal regions previously determined to influence obesity phenotypes, we performed novel Bayesian analyses on the basis of both epistatic and nonepistatic models for four obesity traits: percentage of body fat, adiposity index, total fat mass, and body weight, and also for plasma total cholesterol. The epistatic analysis detected at least one more QTL than the nonepistatic analysis did for all obesity traits. These obesity traits were variously influenced by QTL on chromosomes 2, 7, 12, 15, and 16. Interaction between genes on chromosomes 2 and 12 was present for all obesity traits, accounting for 3-4.8% of the phenotypic variation. Chromosome 12 was found to have weak main effects on all obesity traits. Several different epistatic interactions were also detected for percentage of body fat, adiposity index, and total fat mass. Chromosomes 6 and 12 have not only main effects but also strong epistatic effects on plasma total cholesterol. Our results emphasize the importance of modeling epistasis for discovery of obesity genes.

Adipose Tissue↗
PubMed2003

An EM algorithm for mapping binary disease loci: application to fibrosarcoma in a four-way cross mouse family.

Many diseases show dichotomous phenotypic variation but do not follow a simple Mendelian pattern of inheritance. Variances of these binary diseases are presumably controlled by multiple loci and environmental variants. A least-squares method has been developed for mapping such complex disease loci by treating the binary phenotypes (0 and 1) as if they were continuous. However, the least-squares method is not recommended because of its ad hoc nature. Maximum Likelihood (ML) and Bayesian methods have also been developed for binary disease mapping by incorporating the discrete nature of the phenotypic distribution. In the ML analysis, the likelihood function is usually maximized using some complicated maximization algorithms (e.g. the Newton-Raphson or the simplex algorithm). Under the threshold model of binary disease, we develop an Expectation Maximization (EM) algorithm to solve for the maximum likelihood estimates (MLEs). The new EM algorithm is developed by treating both the unobserved genotype and the disease liability as missing values. As a result, the EM iteration equations have the same form as the normal equation system in linear regression. The EM algorithm is further modified to take into account sexual dimorphism in the linkage maps. Applying the EM-implemented ML method to a four-way-cross mouse family, we detected two regions on the fourth chromosome that have evidence of QTLs controlling the segregation of fibrosarcoma, a form of connective tissue cancer. The two QTLs explain 50-60% of the variance in the disease liability. We also applied a Bayesian method previously developed (modified to take into account sex-specific maps) to this data set and detected one additional QTL on chromosome 13 that explains another 26% of the variance of the disease liability. All the QTLs detected primarily show dominance effects.

Algorithms↗
PubMed2003

Stochastic search variable selection for identifying multiple quantitative trait loci.

In this article, we utilize stochastic search variable selection methodology to develop a Bayesian method for identifying multiple quantitative trait loci (QTL) for complex traits in experimental designs. The proposed procedure entails embedding multiple regression in a hierarchical normal mixture model, where latent indicators for all markers are used to identify the multiple markers. The markers with significant effects can be identified as those with higher posterior probability included in the model. A simple and easy-to-use Gibbs sampler is employed to generate samples from the joint posterior distribution of all unknowns including the latent indicators, genetic effects for all markers, and other model parameters. The proposed method was evaluated using simulated data and illustrated using a real data set. The results demonstrate that the proposed method works well under typical situations of most QTL studies in terms of number of markers and marker density.

Bayes Theorem↗
PubMed2003

Bayesian model choice and search strategies for mapping interacting quantitative trait Loci.

Most complex traits of animals, plants, and humans are influenced by multiple genetic and environmental factors. Interactions among multiple genes play fundamental roles in the genetic control and evolution of complex traits. Statistical modeling of interaction effects in quantitative trait loci (QTL) analysis must accommodate a very large number of potential genetic effects, which presents a major challenge to determining the genetic model with respect to the number of QTL, their positions, and their genetic effects. In this study, we use the methodology of Bayesian model and variable selection to develop strategies for identifying multiple QTL with complex epistatic patterns in experimental designs with two segregating genotypes. Specifically, we develop a reversible jump Markov chain Monte Carlo algorithm to determine the number of QTL and to select main and epistatic effects. With the proposed method, we can jointly infer the genetic model of a complex trait and the associated genetic parameters, including the number, positions, and main and epistatic effects of the identified QTL. Our method can map a large number of QTL with any combination of main and epistatic effects. Utility and flexibility of the method are demonstrated using both simulated data and a real data set. Sensitivity of posterior inference to prior specifications of the number and genetic effects of QTL is investigated.

Bayes Theorem↗
PubMed2002

Mapping quantitative trait loci with epistatic effects.

Epistatic variance can be an important source of variation for complex traits. However, detecting epistatic effects is difficult primarily due to insufficient sample sizes and lack of robust statistical methods. In this paper, we develop a Bayesian method to map multiple quantitative trait loci (QTLs) with epistatic effects. The method can map QTLs in complicated mating designs derived from the cross of two inbred lines. In addition to mapping QTLs for quantitative traits, the proposed method can even map genes underlying binary traits such as disease susceptibility using the threshold model. The parameters of interest are various QTL effects, including additive, dominance and epistatic effects of QTLs, the locations of identified QTLs and even the number of QTLs. When the number of QTLs is treated as an unknown parameter, the dimension of the model becomes a variable. This requires the reversible jump Markov chain Monte Carlo algorithm. The utility of the proposed method is demonstrated through analysis of simulation data.

Algorithms↗
PubMed2002

Linkage analysis of quantitative trait loci in multiple line crosses.

Simple line crosses, for example, backcross and F2, are commonly used in mapping quantitative trait loci (QTL). However, these simple crosses are rarely used alone in commercial plant breeding; rather, crosses involving multiple inbred lines or several simple crosses but connected by shared inbred lines may be common in plant breeding. Mapping QTL using crosses of multiple lines is more relevant to plant breeding. Unfortunately, current statistical methods and computer programs of QTL mapping are all designed for simple line crosses or multiple line crosses but under a regular mating system. It is not straightforward to extend the existing methods to handle multiple line crosses under irregular and complicated mating designs. The major hurdle comes from irregular inbreeding, multiple generations, and multiple alleles. In this study, we develop a Bayesian method implemented via the Markov chain Monte Carlo (MCMC) algorithm for mapping QTL using complicated multiple line crosses. With the MCMC algorithm, we are able to draw a complete path of the gene flow from founder alleles to their descendents via a recursive process. This has greatly simplified the problem caused by irregular mating and inbreeding in the mapping population. Adopting the reversible jump MCMC algorithm, we are able to simultaneously search for multiple QTL along the genome. We can even infer the posterior distribution of the number of QTL, one of the most important parameters in QTL study. Application of the new MCMC based QTL mapping procedure is demonstrated using two different mating designs. Design I involves two inbred lines and their derived F1, F2, and BC populations. Design II is a half-diallel cross involving three inbred lines. The two designs appear different, but can be handled with the same robust computer program.

Algorithms↗