Ina Hoeschele - Academia.edu (original) (raw)

Papers by Ina Hoeschele

Research paper thumbnail of A Note on Algorithms for Genotype and Allele Elimination in Complex Pedigrees with Incomplete Genotype Data

Genetics Society of America, Dec 1, 2000

Elimination of genotypes or alleles for each individual or meiosis, which are inconsistent with o... more Elimination of genotypes or alleles for each individual or meiosis, which are inconsistent with observed genotypes, is a component of various genetic analyses of complex pedigrees. Computational efficiency of the elimination algorithm is critical in some applications such as genotype sampling via descent graph Markov chains. We present an allele elimination algorithm and two genotype elimination algorithms for complex pedigrees with incomplete genotype data. We modify all three algorithms to incorporate inheritance restrictions imposed by a complete or incomplete descent graph such that every inconsistent complete descent graph is detected in any pedigree, and every inconsistent incomplete descent graph is detected in any pedigree without loops with the genotype elimination algorithms. Allele elimination requires less CPU time and memory, but does not always eliminate all inconsistent alleles, even in pedigrees without loops. The first genotype algorithm produces genotype lists for each individual, which are identical to those obtained from the Lange-Goradia algorithm, but exploits the half-sib structure of some populations and reduces CPU time. The second genotype elimination algorithm deletes more inconsistent genotypes in pedigrees with loops and detects more illegal, incomplete descent graphs in such pedigrees.

Research paper thumbnail of Maximum Likelihood Analysis of Rare Binary Traits Under Different Modes of Inheritance

Genetics, 1996

Maximum likelihood methodology was applied to determine the mode of inheritance of rare binary tr... more Maximum likelihood methodology was applied to determine the mode of inheritance of rare binary traits with data structures typical for swine populations. The genetic models considered included a monogenic, a digenic, a polygenic, and three mixed polygenic and major gene models. The main emphasis was on the detection of major genes acting on a polygenic background. Deterministic algorithms were employed to integrate and maximize likelihoods. A simulation study was conducted to evaluate model selection and parameter estimation. Three designs were simulated that differed in the number of sires/number of dams within sires (10/10, 30/30, 100/30). Major gene effects of at least one SD of the liability were detected with satisfactory power under the mixed model of inheritance, except for the smallest design. Parameter estimates were empirically unbiased with acceptable standard errors, except for the smallest design, and allowed to distinguish clearly between the genetic models. Distributi...

Research paper thumbnail of Mapping-Linked Quantitative Trait Loci Using Bayesian Analysis and Markov Chain Monte Carlo Algorithms

Genetics, 1997

A Bayesian method for mapping linked quantitative trait loci (QTL) using multiple linked genetic ... more A Bayesian method for mapping linked quantitative trait loci (QTL) using multiple linked genetic markers is presented. Parameter estimation and hypothesis testing was implemented via Markov chain Monte Carlo (MCMC) algorithms. Parameters included were allele frequencies and substitution effects for two biallelic QTL, map positions of the QTL and markers, allele frequencies of the markers, and polygenic and residual variances. Missing data were polygenic effects and multi-locus marker-QTL genotypes. Three different MCMC schemes for testing the presence of a single or two linked QTL on the chromosome were compared. The first approach includes a model indicator variable representing two unlinked QTL affecting the trait, one linked and one unlinked QTL, or both QTL linked with the markers. The second approach incorporates an indicator variable for each QTL into the model for phenotype, allowing or not allowing for a substitution effect of a QTL on phenotype, and the third approach is ba...

Research paper thumbnail of Adrenocortical Challenge Response and Genomic Analyses in Scottish Terriers With Increased Alkaline Phosphate Activity

Frontiers in veterinary science, 2018

Scottish terriers (ST) frequently have increased serum alkaline phosphatase (ALP) of the steroid ... more Scottish terriers (ST) frequently have increased serum alkaline phosphatase (ALP) of the steroid isoform. Many of these also have high serum concentrations of adrenal sex steroids. The study's objective was to determine the cause of increased sex steroids in ST with increased ALP. Adrenal gland suppression and stimulation were compared by low dose dexamethasone (LDDS), human chorionic gonadotropin (HCG) and adrenocorticotropic hormone (ACTH) response tests. Resting plasma pituitary hormones were measured. Steroidogenesis-related mRNA expression was evaluated in six ST with increased ALP, eight dogs of other breeds with pituitary-dependent hyperadrenocorticism (HAC), and seven normal dogs. The genome-wide association of single nucleotide polymorphisms (SNP) with ALP activity was evaluated in 168 ST. ALP (reference interval 8-70 U/L) was high in all ST (1,054 U/L) and HAC (985 U/L) dogs. All HAC dogs and 2/8 ST had increased cortisol post-ACTH administration. All ST and 2/7 Normal...

Research paper thumbnail of Cross-species transcriptional analysis reveals conserved and host-specific neoplastic processes in mammalian glioma

Scientific reports, Jan 19, 2018

Glioma is a unique neoplastic disease that develops exclusively in the central nervous system (CN... more Glioma is a unique neoplastic disease that develops exclusively in the central nervous system (CNS) and rarely metastasizes to other tissues. This feature strongly implicates the tumor-host CNS microenvironment in gliomagenesis and tumor progression. We investigated the differences and similarities in glioma biology as conveyed by transcriptomic patterns across four mammalian hosts: rats, mice, dogs, and humans. Given the inherent intra-tumoral molecular heterogeneity of human glioma, we focused this study on tumors with upregulation of the platelet-derived growth factor signaling axis, a common and early alteration in human gliomagenesis. The results reveal core neoplastic alterations in mammalian glioma, as well as unique contributions of the tumor host to neoplastic processes. Notable differences were observed in gene expression patterns as well as related biological pathways and cell populations known to mediate key elements of glioma biology, including angiogenesis, immune evas...

Research paper thumbnail of Multiple-trait genetic evaluation for one polychotomous trait and several continuous traits with missing data and unequal models

Journal of Animal Science, 1995

The financial support of the Australian Meat Research Corp. is gratefully acknowledged. We thank ... more The financial support of the Australian Meat Research Corp. is gratefully acknowledged. We thank an anonymous reviewer for a useful contribution.

Research paper thumbnail of Some Model-Based and Distance-Based Clustering Methods for Characterization of Regional Ecological Stressor-Response Patterns and Regional Environmental Quality Trends

Research paper thumbnail of Abstract 53: Transcriptomics and Methylomics of Atherosclerosis in Circulating Monocytes - the Multi-Ethnic Study of Atherosclerosis

Circulation, Mar 10, 2015

Little is known regarding the transcriptional and epigenetic basis for atherogenesis and cardiova... more Little is known regarding the transcriptional and epigenetic basis for atherogenesis and cardiovascular disease (CVD) risk. Here we integrate transcriptomic (Illumina HumanHT-12 v4) and methylomic (Illumina 450K array) data from purified monocytes with concurrent CVD risk factors and measures of atherosclerosis - carotid plaque (CP) identified using ultrasound and coronary artery calcium (CAC), from 1,208 randomly selected participants (554 whites, 260 blacks, 394 Hispanics) of the Multi-Ethnic Study of Atherosclerosis (MESA). Association analysis was performed using linear and logistic regression, adjusting for demographics, technical covariates, and other known CVD risk factors. A false discovery rate (FDR) <0.05 was used to control for multiple comparisons. RESULTS: We identified expression of two genes, ARID5B (a transcription factor) and PDLIM7, positively associated with both CP and CAC, and 17 additional genes associated with only CAC . We also identified 29 and seven differentially methylated CpGs associated with CP and CAC, respectively, including a CpG at ILVBL associated with both CP and CAC. Eleven of these atherosclerosis CpGs were also associated with cis-gene expression, including an ARID5B expression-associated methylation site (cg25953130, ARID5B intron) which overlapped a predicted strong enhancer, a transcription factor binding site (for EP300), and a DNase I hotspot (ENCODE and BLUEPRINT monocyte data). The inverse association between methylation of this ARID5B CpG and atherosclerosis (CP:p=4.3x10-7, FDR=0.01; CAC: p= 2.4x10-5, FDR=0.32) appeared to be mediated through ARID5B expression (CP: p=2.1x10-4, CAC: p=2.1 x10-3, using Structural Equation modeling with bootstrapping). Furthermore, many other known risk factors for CVD (age, ethnicity, body mass index, diabetes, HDL, and interleukin-6 levels) were also associated with ARID5B expression at genome-wide levels of significance. The ARID5B associations with atherosclerosis at gene expression and methylation levels together explain an additional 2.3% variability in CP above and beyond known CVD risk factors, and were consistent across age (< or ≥65 years), sex, race/ethnicity, CVD status, or statin use subgroups, as well as the independent sites of data collection. ARID5B expression was also positively associated with prevalent CVD (p=0.006). CONCLUSIONS: The concurrent multi-omic profiling of atherogenic-related cells coupled with state-of-the-art measurements of atherosclerosis in a large, well-phenotyped, multi-ethnic cohort provide novel insights into the biomarkers and the potential molecular mechanisms of atherosclerosis. In particular, our data on ARID5B , taken together with previously reported experimental evidence for its role in promoting lipid accumulation and smooth muscle cell differentiation, strongly suggests an atherogenic role for this gene.

Research paper thumbnail of Elimination of Quantitative Trait Loci Equations in an Animal Model Incorporating Genetic Marker Data

Journal of Dairy Science, 1993

An animal model for BLUP of additive effects at marked quantitative trait loci and breeding value... more An animal model for BLUP of additive effects at marked quantitative trait loci and breeding values does not require quantitative trait loci equations for animals that were not marker genotyped and do not provide relationship ties among genotyped descendants. An animal model in quantitative trait loci effects and breeding values is equivalent to a previous model in quantitative trait loci effects and residual breeding values. With no marker data, absorption of quantitative trait loci into breeding value equations reduces to the standard animal model for phenotypic data. With marker data on some animals. quantitative trait loci equations for animals without marker data and not providing relationship ties among genotyped descendants can be eliminated. Resulting mixed model equations contain the inverse of a variance-covariance matrix among breeding values and remaining quantitative trait loci effects. which can be computed directly. Quantitative trait loci effects of progeny with parental quantitative trait loci effects eliminated are linked to breeding values of parents. Animals without marker data may be ancestors and nonelite members of the current population. Hence, a substantial fraction of a population may not be genotyped. Then, the number of equations is reduced considerably.

Research paper thumbnail of Association of Genetic Defects with Yield and Type Traits: The Weaver Locus Effect on Yield

Journal of Dairy Science, 1990

The association of recessive genetic disorders with yield and type traits was investigated. The f... more The association of recessive genetic disorders with yield and type traits was investigated. The frequency of a defective gene could be increased by selection if it is positively associated with selected traits, despite efforts to reduce it. Genetic defects considered were weaver in Brown Swiss and rectovaginal constriction and limber leg in Jerseys. Data sets for linkage analysis consisted of 245 sons of 9 carrier sires, 1036 sons of 16 carrier sires, and 557 sons of 10 carrier sires, respectively. Weaver carrier sons had higher producing daughters than noncarrier sons within all 9 sire families. Weaver carrier cows have an advantage of 673.6 kg milk and 26.0 kg fat and a disadvantage in rear legs score, indicating that the condition may not be completely recessive. Carriers of the other defect genes have no advantage for milk production, are scored lower for pelvic angle, and limber leg carriers have more desirable udders. Estimates of defect gene frequencies in 264,000 Jersey cows show a decrease over time for rectovaginal constriction and limber leg; in 97,723 Brown Swiss cows, frequency of the weaver gene increased over time. Gene frequencies in daughters of the youngest sires were 5.48, 2.13, and 8.89%, respectively. Consistently higher yield evaluations of weaver carrier sons within each sire family, large advantage in production of weaver carrier cows, and increasing gene frequency over time indicate that a chromosome segment with major effect on yield is tightly linked to weaver in Brown Swiss.

Research paper thumbnail of Potential Gain from Insertion of Major Genes into Dairy Cattle

Journal of Dairy Science, 1990

ABSTRACT

Research paper thumbnail of Utilization of Dominance Variance Through Mate Allocation Strategies

Journal of Dairy Science, 1992

Simulation was used to evaluate the increase in progeny perfonnance from three mating strategies ... more Simulation was used to evaluate the increase in progeny perfonnance from three mating strategies based on predicted specific combining abilities among sires and maternal grandsires over random mating that do not use specific combining ability but avoid inbreeding. Specific combining abilities were equal to the sum of combination effects from dominance plus the effect of inbreeding depression. Mates were allocated by linear programming with two a~proximations. Genetic parameters were h in the narrow sense equal to .05, .15, or .25 and the ratio of dominance to phenotypic variance equal to .05, .10, or .15. A population of 400 bulls were grouped by .99, .85, and .70 PTA reliability; the first group was sires and maternal grandsires of others. Recurrence equations for combination effects that were due to dominance, not including inbreeding depression, were used to create a matrix of true combination effects among bulls. Predicted specific combining abilities were computed from true combination effects using low, intermediate, and high levels of accuracy plus the effect of inbreeding. Twenty herds of cows were generated for each bull population. Within a herd, four mating groups of 123 cows were mated to 10 bulls from all bull groups. TIle three mating strategies yielded progeny merits slightly but significantly higher than random mating. Scaled by standard deviation of milk yield, increases with linear programming

Research paper thumbnail of Additive and Nonadditive Genetic Variance in Female Fertility of Holsteins

Journal of Dairy Science, 1991

Additive and nonadditive genetic variances were estimated for cow fertility of Holsteins. Measure... more Additive and nonadditive genetic variances were estimated for cow fertility of Holsteins. Measures of fertility were first lactation days open and service period as recorded and with upper bounds of 150 and 91 d, respectively. Six million inseminations from the Raleigh, North Carolina Processing Center were used to form fertility records of 379,009 cows. Data were analyzed with a model accounting for all additive, dominance, and additive by additive covariances traced through sires and maternal grandsires. Variance components were estimated by the tilde-hat approximation to REML. Heritability in the narrow sense was 2% for days open and .8% for service period. Dominance and additive by additive variance as a percentage of phenotypic variation strongly depended on imposition of upper bounds. Heritabilities in the broad sense ranged from 2.2 to 6.6% and were at least twice as large as heritabilities in the narrow sense. Effect of 25% inbreeding was only around an additional 3 d open. Specific combining abilities among bulls were estimated as sums of dominance and additive by additive interactions removing effect of inbreeding depression. Differences between maximum and minimum estimates were in the order of twice the estimated standard deviation, ranging from 1.5 to 6.7 d. Effects of inbreeding and specific combining ability could be jointly considered in mating programs following sire selection.

Research paper thumbnail of Mapping Quantitative Trait Loci in Outbred Pedigrees

Handbook of Statistical Genetics, 2004

In this chapter, we present statistical methods for mapping quantitative trait loci (QTLs) in out... more In this chapter, we present statistical methods for mapping quantitative trait loci (QTLs) in outbred or complex pedigrees. Such pedigrees exist primarily in livestock populations, also in human populations, and occasionally in experimental animal or plant populations. The main focus of this chapter is on linkage mapping, but methods for linkage disequilibrium (LD) and combined linkage/LD mapping are also outlined. The latter are very recent proposals and are at the time of writing less developed than linkage methods. We describe least-squares and maximum likelihood (ML) methods for estimating QTL effects, and variance components analysis by approximate (residual) ML for estimating QTL variance contributions. We describe Bayesian QTL mapping, its prior distributions and other distributional assumptions, its implementation via Markov chain Monte Carlo (MCMC) algorithms, its inferences, and contrast it with frequentist methodology. Genotype sampling algorithms using genotypic peeling, allelic peeling, or descent graphs are described. Genotype samplers are a critical component of MCMC algorithms implementing ML and Bayesian analyses for complex pedigrees. Lastly, fine-mapping methods including chromosome dissection and linkage disequilibrium mapping using current and historical recombinations, respectively, are outlined, and initial method developments combining linkage disequilibrium and linkage are presented. Keywords: quantitative trait loci; pedigree analysis; Bayesian inference; variance components; residual maximum likelihood; outbred population; linkage mapping; linkage disequilibrium; Markov chain monte carlo; peeling; descent graph

Research paper thumbnail of A comparison of efficient genotype samplers for complex pedigrees and multiple linked loci

Research paper thumbnail of Genetic Architecture of Complex Diseases

Analysis of Complex Disease Association Studies, 2011

Research paper thumbnail of Simulation of the Benchmark Datasets

Gene Network Inference, 2013

In this chapter, the in silico systems genetics dataset, used as a benchmark in the rest of the b... more In this chapter, the in silico systems genetics dataset, used as a benchmark in the rest of the book, is described in detail, in particular regarding its simulation by SysGenSIM. Morever, the algorithms underlying the generation of the gene expression data and the genotype values are fully illustrated.

Research paper thumbnail of Finite mixture model analysis of microarray expression data on samples of uncertain biological type with application to reproductive efficiency

Veterinary Immunology and Immunopathology, 2005

Common goals of microarray experiments are the detection of genes that are differentially express... more Common goals of microarray experiments are the detection of genes that are differentially expressed between several biological types and the construction of classifiers that predict biological type of samples. Here we consider a situation where there is no training data. There is considerable interest in comparing expression profiles associated with successful pregnancies (SP) and unsuccessful pregnancies (UP) in model and farm animals. Successful pregnancy rate is known to be much higher in embryos generated by in vitro fertilization (IVF) than in nuclear transfer (NT) embryos, and higher under induced ovulation for large follicles (LF) than for small follicles (SF). The tasks of identifying genes differentially expressed between SP and UP, and predicting SP for future samples are not well accomplished by comparing IVF and NT, or LF and SF. A suitable method is finite mixture model analysis (FMMA), which models each observed class (IVF and NT, or LF and SF) as a mixture of two distributions, one for SP and one for UP, with different known or unknown proportions (here known to be 0.50 SP for IVF and 0.02 SP for NT). The means of the two distributions differ for the differentially expressed genes, which we identify via a likelihood ratio test. We confirm by simulation that FMMA strongly outperforms hierarchical clustering and linear discriminant analysis using the known class labels (NT, IVF). We apply FMMA to a real data set on IVF and NT embryos, and compute their posterior probabilities of SP, which confirm our prior knowledge of the SP proportions for IVF and NT.

Research paper thumbnail of Genetic evaluation methods for populations with dominance and inbreeding

Theoretical and Applied Genetics, 1993

The effect of inbreeding on mean and genetic covariance matrix for a quantitative trait in a popu... more The effect of inbreeding on mean and genetic covariance matrix for a quantitative trait in a population with additive and dominance effects is shown. This genetic covariance matrix is a function of five relationship matrices and five genetic parameters describing the population. Elements of the relationship matrices are functions of Gillois' (1964) identity coefficients for the four genes at a locus in two individuals. The equivalence of the path coefficient method (Jacquard 1966) and the tabular method (Smith and Mfiki-Tanila 1990) to compute the covariance matrix of additive and dominance effects in a population with inbreeding is shown. The tabular method is modified to compute relationship matrices rather than the covariance matrix, which is trait dependent. Finally, approximate and exact Best Linear Unbiased Predictions (BLUP) of additive and dominance effects are compared using simulated data with inbreeding but no directional selection. The trait simulated was affected by 64 unlinked bialMic loci with equal effect and complete dominance. Simulated average inbreeding levels ranged from zero in generation one to 0.35 in generation five. The approximate method only accounted for the effect of inbreeding on mean and additive genetic covariance matrix, whereas the exact accounted for all of the changes in mean and genetic covariance matrix due to inbreeding. Approximate BLUP, which is computable for large populations where exact BLUP is not feasible, yielded unbiased predictions of additive and dominance effects in each generation with only slightly reduced accuracies relative to exact BLUP.

Research paper thumbnail of A Monte Carlo method for Bayesian analysis of linkage between single markers and quantitative trait loci. I. Methodology

Theoretical and Applied Genetics, 1996

A Bayesian approach to the statistical mapping of Quantitative Trait Loci (QTLs) using single mar... more A Bayesian approach to the statistical mapping of Quantitative Trait Loci (QTLs) using single markers was implemented via Markov Chain Monte Carlo (MCMC) algorithms for parameter estimation and hypothesis testing. Parameter estimators were marginal posterior means computed using a Gibbs sampler with data augmentation. Variables sampled included the augmented data (marker-QTL genotypes, polygenic effects), an indicator variable for linkage, and the parameters (allele frequency, QTL substitution effect, recombination rate, polygenic and residual variances). Several MCMC algorithms were derived for computing Bayesian tests of linkage, which consisted of the marginal posterior probability of linkage and the marginal likelihood of the QTL variance associated with the marker.

Research paper thumbnail of A Note on Algorithms for Genotype and Allele Elimination in Complex Pedigrees with Incomplete Genotype Data

Genetics Society of America, Dec 1, 2000

Elimination of genotypes or alleles for each individual or meiosis, which are inconsistent with o... more Elimination of genotypes or alleles for each individual or meiosis, which are inconsistent with observed genotypes, is a component of various genetic analyses of complex pedigrees. Computational efficiency of the elimination algorithm is critical in some applications such as genotype sampling via descent graph Markov chains. We present an allele elimination algorithm and two genotype elimination algorithms for complex pedigrees with incomplete genotype data. We modify all three algorithms to incorporate inheritance restrictions imposed by a complete or incomplete descent graph such that every inconsistent complete descent graph is detected in any pedigree, and every inconsistent incomplete descent graph is detected in any pedigree without loops with the genotype elimination algorithms. Allele elimination requires less CPU time and memory, but does not always eliminate all inconsistent alleles, even in pedigrees without loops. The first genotype algorithm produces genotype lists for each individual, which are identical to those obtained from the Lange-Goradia algorithm, but exploits the half-sib structure of some populations and reduces CPU time. The second genotype elimination algorithm deletes more inconsistent genotypes in pedigrees with loops and detects more illegal, incomplete descent graphs in such pedigrees.

Research paper thumbnail of Maximum Likelihood Analysis of Rare Binary Traits Under Different Modes of Inheritance

Genetics, 1996

Maximum likelihood methodology was applied to determine the mode of inheritance of rare binary tr... more Maximum likelihood methodology was applied to determine the mode of inheritance of rare binary traits with data structures typical for swine populations. The genetic models considered included a monogenic, a digenic, a polygenic, and three mixed polygenic and major gene models. The main emphasis was on the detection of major genes acting on a polygenic background. Deterministic algorithms were employed to integrate and maximize likelihoods. A simulation study was conducted to evaluate model selection and parameter estimation. Three designs were simulated that differed in the number of sires/number of dams within sires (10/10, 30/30, 100/30). Major gene effects of at least one SD of the liability were detected with satisfactory power under the mixed model of inheritance, except for the smallest design. Parameter estimates were empirically unbiased with acceptable standard errors, except for the smallest design, and allowed to distinguish clearly between the genetic models. Distributi...

Research paper thumbnail of Mapping-Linked Quantitative Trait Loci Using Bayesian Analysis and Markov Chain Monte Carlo Algorithms

Genetics, 1997

A Bayesian method for mapping linked quantitative trait loci (QTL) using multiple linked genetic ... more A Bayesian method for mapping linked quantitative trait loci (QTL) using multiple linked genetic markers is presented. Parameter estimation and hypothesis testing was implemented via Markov chain Monte Carlo (MCMC) algorithms. Parameters included were allele frequencies and substitution effects for two biallelic QTL, map positions of the QTL and markers, allele frequencies of the markers, and polygenic and residual variances. Missing data were polygenic effects and multi-locus marker-QTL genotypes. Three different MCMC schemes for testing the presence of a single or two linked QTL on the chromosome were compared. The first approach includes a model indicator variable representing two unlinked QTL affecting the trait, one linked and one unlinked QTL, or both QTL linked with the markers. The second approach incorporates an indicator variable for each QTL into the model for phenotype, allowing or not allowing for a substitution effect of a QTL on phenotype, and the third approach is ba...

Research paper thumbnail of Adrenocortical Challenge Response and Genomic Analyses in Scottish Terriers With Increased Alkaline Phosphate Activity

Frontiers in veterinary science, 2018

Scottish terriers (ST) frequently have increased serum alkaline phosphatase (ALP) of the steroid ... more Scottish terriers (ST) frequently have increased serum alkaline phosphatase (ALP) of the steroid isoform. Many of these also have high serum concentrations of adrenal sex steroids. The study's objective was to determine the cause of increased sex steroids in ST with increased ALP. Adrenal gland suppression and stimulation were compared by low dose dexamethasone (LDDS), human chorionic gonadotropin (HCG) and adrenocorticotropic hormone (ACTH) response tests. Resting plasma pituitary hormones were measured. Steroidogenesis-related mRNA expression was evaluated in six ST with increased ALP, eight dogs of other breeds with pituitary-dependent hyperadrenocorticism (HAC), and seven normal dogs. The genome-wide association of single nucleotide polymorphisms (SNP) with ALP activity was evaluated in 168 ST. ALP (reference interval 8-70 U/L) was high in all ST (1,054 U/L) and HAC (985 U/L) dogs. All HAC dogs and 2/8 ST had increased cortisol post-ACTH administration. All ST and 2/7 Normal...

Research paper thumbnail of Cross-species transcriptional analysis reveals conserved and host-specific neoplastic processes in mammalian glioma

Scientific reports, Jan 19, 2018

Glioma is a unique neoplastic disease that develops exclusively in the central nervous system (CN... more Glioma is a unique neoplastic disease that develops exclusively in the central nervous system (CNS) and rarely metastasizes to other tissues. This feature strongly implicates the tumor-host CNS microenvironment in gliomagenesis and tumor progression. We investigated the differences and similarities in glioma biology as conveyed by transcriptomic patterns across four mammalian hosts: rats, mice, dogs, and humans. Given the inherent intra-tumoral molecular heterogeneity of human glioma, we focused this study on tumors with upregulation of the platelet-derived growth factor signaling axis, a common and early alteration in human gliomagenesis. The results reveal core neoplastic alterations in mammalian glioma, as well as unique contributions of the tumor host to neoplastic processes. Notable differences were observed in gene expression patterns as well as related biological pathways and cell populations known to mediate key elements of glioma biology, including angiogenesis, immune evas...

Research paper thumbnail of Multiple-trait genetic evaluation for one polychotomous trait and several continuous traits with missing data and unequal models

Journal of Animal Science, 1995

The financial support of the Australian Meat Research Corp. is gratefully acknowledged. We thank ... more The financial support of the Australian Meat Research Corp. is gratefully acknowledged. We thank an anonymous reviewer for a useful contribution.

Research paper thumbnail of Some Model-Based and Distance-Based Clustering Methods for Characterization of Regional Ecological Stressor-Response Patterns and Regional Environmental Quality Trends

Research paper thumbnail of Abstract 53: Transcriptomics and Methylomics of Atherosclerosis in Circulating Monocytes - the Multi-Ethnic Study of Atherosclerosis

Circulation, Mar 10, 2015

Little is known regarding the transcriptional and epigenetic basis for atherogenesis and cardiova... more Little is known regarding the transcriptional and epigenetic basis for atherogenesis and cardiovascular disease (CVD) risk. Here we integrate transcriptomic (Illumina HumanHT-12 v4) and methylomic (Illumina 450K array) data from purified monocytes with concurrent CVD risk factors and measures of atherosclerosis - carotid plaque (CP) identified using ultrasound and coronary artery calcium (CAC), from 1,208 randomly selected participants (554 whites, 260 blacks, 394 Hispanics) of the Multi-Ethnic Study of Atherosclerosis (MESA). Association analysis was performed using linear and logistic regression, adjusting for demographics, technical covariates, and other known CVD risk factors. A false discovery rate (FDR) <0.05 was used to control for multiple comparisons. RESULTS: We identified expression of two genes, ARID5B (a transcription factor) and PDLIM7, positively associated with both CP and CAC, and 17 additional genes associated with only CAC . We also identified 29 and seven differentially methylated CpGs associated with CP and CAC, respectively, including a CpG at ILVBL associated with both CP and CAC. Eleven of these atherosclerosis CpGs were also associated with cis-gene expression, including an ARID5B expression-associated methylation site (cg25953130, ARID5B intron) which overlapped a predicted strong enhancer, a transcription factor binding site (for EP300), and a DNase I hotspot (ENCODE and BLUEPRINT monocyte data). The inverse association between methylation of this ARID5B CpG and atherosclerosis (CP:p=4.3x10-7, FDR=0.01; CAC: p= 2.4x10-5, FDR=0.32) appeared to be mediated through ARID5B expression (CP: p=2.1x10-4, CAC: p=2.1 x10-3, using Structural Equation modeling with bootstrapping). Furthermore, many other known risk factors for CVD (age, ethnicity, body mass index, diabetes, HDL, and interleukin-6 levels) were also associated with ARID5B expression at genome-wide levels of significance. The ARID5B associations with atherosclerosis at gene expression and methylation levels together explain an additional 2.3% variability in CP above and beyond known CVD risk factors, and were consistent across age (< or ≥65 years), sex, race/ethnicity, CVD status, or statin use subgroups, as well as the independent sites of data collection. ARID5B expression was also positively associated with prevalent CVD (p=0.006). CONCLUSIONS: The concurrent multi-omic profiling of atherogenic-related cells coupled with state-of-the-art measurements of atherosclerosis in a large, well-phenotyped, multi-ethnic cohort provide novel insights into the biomarkers and the potential molecular mechanisms of atherosclerosis. In particular, our data on ARID5B , taken together with previously reported experimental evidence for its role in promoting lipid accumulation and smooth muscle cell differentiation, strongly suggests an atherogenic role for this gene.

Research paper thumbnail of Elimination of Quantitative Trait Loci Equations in an Animal Model Incorporating Genetic Marker Data

Journal of Dairy Science, 1993

An animal model for BLUP of additive effects at marked quantitative trait loci and breeding value... more An animal model for BLUP of additive effects at marked quantitative trait loci and breeding values does not require quantitative trait loci equations for animals that were not marker genotyped and do not provide relationship ties among genotyped descendants. An animal model in quantitative trait loci effects and breeding values is equivalent to a previous model in quantitative trait loci effects and residual breeding values. With no marker data, absorption of quantitative trait loci into breeding value equations reduces to the standard animal model for phenotypic data. With marker data on some animals. quantitative trait loci equations for animals without marker data and not providing relationship ties among genotyped descendants can be eliminated. Resulting mixed model equations contain the inverse of a variance-covariance matrix among breeding values and remaining quantitative trait loci effects. which can be computed directly. Quantitative trait loci effects of progeny with parental quantitative trait loci effects eliminated are linked to breeding values of parents. Animals without marker data may be ancestors and nonelite members of the current population. Hence, a substantial fraction of a population may not be genotyped. Then, the number of equations is reduced considerably.

Research paper thumbnail of Association of Genetic Defects with Yield and Type Traits: The Weaver Locus Effect on Yield

Journal of Dairy Science, 1990

The association of recessive genetic disorders with yield and type traits was investigated. The f... more The association of recessive genetic disorders with yield and type traits was investigated. The frequency of a defective gene could be increased by selection if it is positively associated with selected traits, despite efforts to reduce it. Genetic defects considered were weaver in Brown Swiss and rectovaginal constriction and limber leg in Jerseys. Data sets for linkage analysis consisted of 245 sons of 9 carrier sires, 1036 sons of 16 carrier sires, and 557 sons of 10 carrier sires, respectively. Weaver carrier sons had higher producing daughters than noncarrier sons within all 9 sire families. Weaver carrier cows have an advantage of 673.6 kg milk and 26.0 kg fat and a disadvantage in rear legs score, indicating that the condition may not be completely recessive. Carriers of the other defect genes have no advantage for milk production, are scored lower for pelvic angle, and limber leg carriers have more desirable udders. Estimates of defect gene frequencies in 264,000 Jersey cows show a decrease over time for rectovaginal constriction and limber leg; in 97,723 Brown Swiss cows, frequency of the weaver gene increased over time. Gene frequencies in daughters of the youngest sires were 5.48, 2.13, and 8.89%, respectively. Consistently higher yield evaluations of weaver carrier sons within each sire family, large advantage in production of weaver carrier cows, and increasing gene frequency over time indicate that a chromosome segment with major effect on yield is tightly linked to weaver in Brown Swiss.

Research paper thumbnail of Potential Gain from Insertion of Major Genes into Dairy Cattle

Journal of Dairy Science, 1990

ABSTRACT

Research paper thumbnail of Utilization of Dominance Variance Through Mate Allocation Strategies

Journal of Dairy Science, 1992

Simulation was used to evaluate the increase in progeny perfonnance from three mating strategies ... more Simulation was used to evaluate the increase in progeny perfonnance from three mating strategies based on predicted specific combining abilities among sires and maternal grandsires over random mating that do not use specific combining ability but avoid inbreeding. Specific combining abilities were equal to the sum of combination effects from dominance plus the effect of inbreeding depression. Mates were allocated by linear programming with two a~proximations. Genetic parameters were h in the narrow sense equal to .05, .15, or .25 and the ratio of dominance to phenotypic variance equal to .05, .10, or .15. A population of 400 bulls were grouped by .99, .85, and .70 PTA reliability; the first group was sires and maternal grandsires of others. Recurrence equations for combination effects that were due to dominance, not including inbreeding depression, were used to create a matrix of true combination effects among bulls. Predicted specific combining abilities were computed from true combination effects using low, intermediate, and high levels of accuracy plus the effect of inbreeding. Twenty herds of cows were generated for each bull population. Within a herd, four mating groups of 123 cows were mated to 10 bulls from all bull groups. TIle three mating strategies yielded progeny merits slightly but significantly higher than random mating. Scaled by standard deviation of milk yield, increases with linear programming

Research paper thumbnail of Additive and Nonadditive Genetic Variance in Female Fertility of Holsteins

Journal of Dairy Science, 1991

Additive and nonadditive genetic variances were estimated for cow fertility of Holsteins. Measure... more Additive and nonadditive genetic variances were estimated for cow fertility of Holsteins. Measures of fertility were first lactation days open and service period as recorded and with upper bounds of 150 and 91 d, respectively. Six million inseminations from the Raleigh, North Carolina Processing Center were used to form fertility records of 379,009 cows. Data were analyzed with a model accounting for all additive, dominance, and additive by additive covariances traced through sires and maternal grandsires. Variance components were estimated by the tilde-hat approximation to REML. Heritability in the narrow sense was 2% for days open and .8% for service period. Dominance and additive by additive variance as a percentage of phenotypic variation strongly depended on imposition of upper bounds. Heritabilities in the broad sense ranged from 2.2 to 6.6% and were at least twice as large as heritabilities in the narrow sense. Effect of 25% inbreeding was only around an additional 3 d open. Specific combining abilities among bulls were estimated as sums of dominance and additive by additive interactions removing effect of inbreeding depression. Differences between maximum and minimum estimates were in the order of twice the estimated standard deviation, ranging from 1.5 to 6.7 d. Effects of inbreeding and specific combining ability could be jointly considered in mating programs following sire selection.

Research paper thumbnail of Mapping Quantitative Trait Loci in Outbred Pedigrees

Handbook of Statistical Genetics, 2004

In this chapter, we present statistical methods for mapping quantitative trait loci (QTLs) in out... more In this chapter, we present statistical methods for mapping quantitative trait loci (QTLs) in outbred or complex pedigrees. Such pedigrees exist primarily in livestock populations, also in human populations, and occasionally in experimental animal or plant populations. The main focus of this chapter is on linkage mapping, but methods for linkage disequilibrium (LD) and combined linkage/LD mapping are also outlined. The latter are very recent proposals and are at the time of writing less developed than linkage methods. We describe least-squares and maximum likelihood (ML) methods for estimating QTL effects, and variance components analysis by approximate (residual) ML for estimating QTL variance contributions. We describe Bayesian QTL mapping, its prior distributions and other distributional assumptions, its implementation via Markov chain Monte Carlo (MCMC) algorithms, its inferences, and contrast it with frequentist methodology. Genotype sampling algorithms using genotypic peeling, allelic peeling, or descent graphs are described. Genotype samplers are a critical component of MCMC algorithms implementing ML and Bayesian analyses for complex pedigrees. Lastly, fine-mapping methods including chromosome dissection and linkage disequilibrium mapping using current and historical recombinations, respectively, are outlined, and initial method developments combining linkage disequilibrium and linkage are presented. Keywords: quantitative trait loci; pedigree analysis; Bayesian inference; variance components; residual maximum likelihood; outbred population; linkage mapping; linkage disequilibrium; Markov chain monte carlo; peeling; descent graph

Research paper thumbnail of A comparison of efficient genotype samplers for complex pedigrees and multiple linked loci

Research paper thumbnail of Genetic Architecture of Complex Diseases

Analysis of Complex Disease Association Studies, 2011

Research paper thumbnail of Simulation of the Benchmark Datasets

Gene Network Inference, 2013

In this chapter, the in silico systems genetics dataset, used as a benchmark in the rest of the b... more In this chapter, the in silico systems genetics dataset, used as a benchmark in the rest of the book, is described in detail, in particular regarding its simulation by SysGenSIM. Morever, the algorithms underlying the generation of the gene expression data and the genotype values are fully illustrated.

Research paper thumbnail of Finite mixture model analysis of microarray expression data on samples of uncertain biological type with application to reproductive efficiency

Veterinary Immunology and Immunopathology, 2005

Common goals of microarray experiments are the detection of genes that are differentially express... more Common goals of microarray experiments are the detection of genes that are differentially expressed between several biological types and the construction of classifiers that predict biological type of samples. Here we consider a situation where there is no training data. There is considerable interest in comparing expression profiles associated with successful pregnancies (SP) and unsuccessful pregnancies (UP) in model and farm animals. Successful pregnancy rate is known to be much higher in embryos generated by in vitro fertilization (IVF) than in nuclear transfer (NT) embryos, and higher under induced ovulation for large follicles (LF) than for small follicles (SF). The tasks of identifying genes differentially expressed between SP and UP, and predicting SP for future samples are not well accomplished by comparing IVF and NT, or LF and SF. A suitable method is finite mixture model analysis (FMMA), which models each observed class (IVF and NT, or LF and SF) as a mixture of two distributions, one for SP and one for UP, with different known or unknown proportions (here known to be 0.50 SP for IVF and 0.02 SP for NT). The means of the two distributions differ for the differentially expressed genes, which we identify via a likelihood ratio test. We confirm by simulation that FMMA strongly outperforms hierarchical clustering and linear discriminant analysis using the known class labels (NT, IVF). We apply FMMA to a real data set on IVF and NT embryos, and compute their posterior probabilities of SP, which confirm our prior knowledge of the SP proportions for IVF and NT.

Research paper thumbnail of Genetic evaluation methods for populations with dominance and inbreeding

Theoretical and Applied Genetics, 1993

The effect of inbreeding on mean and genetic covariance matrix for a quantitative trait in a popu... more The effect of inbreeding on mean and genetic covariance matrix for a quantitative trait in a population with additive and dominance effects is shown. This genetic covariance matrix is a function of five relationship matrices and five genetic parameters describing the population. Elements of the relationship matrices are functions of Gillois' (1964) identity coefficients for the four genes at a locus in two individuals. The equivalence of the path coefficient method (Jacquard 1966) and the tabular method (Smith and Mfiki-Tanila 1990) to compute the covariance matrix of additive and dominance effects in a population with inbreeding is shown. The tabular method is modified to compute relationship matrices rather than the covariance matrix, which is trait dependent. Finally, approximate and exact Best Linear Unbiased Predictions (BLUP) of additive and dominance effects are compared using simulated data with inbreeding but no directional selection. The trait simulated was affected by 64 unlinked bialMic loci with equal effect and complete dominance. Simulated average inbreeding levels ranged from zero in generation one to 0.35 in generation five. The approximate method only accounted for the effect of inbreeding on mean and additive genetic covariance matrix, whereas the exact accounted for all of the changes in mean and genetic covariance matrix due to inbreeding. Approximate BLUP, which is computable for large populations where exact BLUP is not feasible, yielded unbiased predictions of additive and dominance effects in each generation with only slightly reduced accuracies relative to exact BLUP.

Research paper thumbnail of A Monte Carlo method for Bayesian analysis of linkage between single markers and quantitative trait loci. I. Methodology

Theoretical and Applied Genetics, 1996

A Bayesian approach to the statistical mapping of Quantitative Trait Loci (QTLs) using single mar... more A Bayesian approach to the statistical mapping of Quantitative Trait Loci (QTLs) using single markers was implemented via Markov Chain Monte Carlo (MCMC) algorithms for parameter estimation and hypothesis testing. Parameter estimators were marginal posterior means computed using a Gibbs sampler with data augmentation. Variables sampled included the augmented data (marker-QTL genotypes, polygenic effects), an indicator variable for linkage, and the parameters (allele frequency, QTL substitution effect, recombination rate, polygenic and residual variances). Several MCMC algorithms were derived for computing Bayesian tests of linkage, which consisted of the marginal posterior probability of linkage and the marginal likelihood of the QTL variance associated with the marker.