Dahlia M. Nielsen

A unified mixed-model method for association mapping that accounts for multiple levels of relatedness

As population structure can result in spurious associations, it has constrained the use of association studies in human and plant genetics. Association mapping, however, holds great promise if true signals of functional association can be separated from the vast number of false signals generated by population structure. We have developed a unified mixed-model approach to account for multiple levels of relatedness simultaneously as detected by random genetic markers. We applied this new approach to two samples: a family-based sample of 14 human families, for quantitative gene expression dissection, and a sample of 277 diverse maize inbred lines with complex familial relationships and population structure, for quantitative trait dissection. Our method demonstrates improved control of both type I and type II error rates over other methods. As this new method crosses the boundary between family-based and structured association samples, it provides a powerful complement to currently available methods for association mapping.

Detecting Marker-Disease Association by Testing for Hardy-Weinberg Disequilibrium at a Marker Locus

We review and extend a recent suggestion that fine-scale localization of a disease-susceptibility locus for a complex disease be done on the basis of deviations from Hardy-Weinberg equilibrium among affected individuals. This deviation is driven by linkage disequilibrium between disease and marker loci in the whole population and requires a heterogeneous genetic basis for the disease. A finding of marker-locus Hardy-Weinberg disequilibrium therefore implies disease heterogeneity and marker-disease linkage disequilibrium. Although a lack of departure of Hardy-Weinberg disequilibrium at marker loci implies that disease susceptibilityweighted linkage disequilibria are zero, given disease heterogeneity, it does not follow that the usual measures of linkage disequilibrium are zero. For disease-susceptibility loci with more than two alleles, therefore, care is needed in the drawing of inferences from marker Hardy-Weinberg disequilibria.

Genomic Hotspots for Adaptation: The Population Genetics of Mullerian Mimicry in Heliconius erato

Wing pattern evolution in Heliconius butterflies provides some of the most striking examples of adaptation by natural selection. The genes controlling pattern variation are classic examples of Mendelian loci of large effect, where allelic variation causes large and discrete phenotypic changes and is responsible for both convergent and highly divergent wing pattern evolution across the genus. We characterize nucleotide variation, genotype-by-phenotype associations, linkage disequilibrium (LD), and candidate gene expression patterns across two unlinked genomic intervals that control yellow and red wing pattern variation among mimetic forms of Heliconius erato. Despite very strong natural selection on color pattern, we see neither a strong reduction in genetic diversity nor evidence for extended LD across either patterning interval. This observation highlights the extent that recombination can erase the signature of selection in natural populations and is consistent with the hypothesis that either the adaptive radiation or the alleles controlling it are quite old. However, across both patterning intervals we identified SNPs clustered in several coding regions that were strongly associated with color pattern phenotype. Interestingly, coding regions with associated SNPs were widely separated, suggesting that color pattern alleles may be composed of multiple functional sites, conforming to previous descriptions of these loci as “supergenes.” Examination of gene expression levels of genes flanking these regions in both H. erato and its co-mimic, H. melpomene, implicate a gene with high sequence similarity to a kinesin as playing a key role in modulating pattern and provides convincing evidence for parallel changes in gene regulation across co-mimetic lineages. The complex genetic architecture at these color pattern loci stands in marked contrast to the single casual mutations often identified in genetic studies of adaptation, but may be more indicative of the type of genetic changes responsible for much of the adaptive variation found in natural populations.

Genetic Polymorphisms and the Risk of Stroke After Cardiac Surgery

Background and Purpose— Stroke represents a significant cause of morbidity and mortality after cardiac surgery. Although the risk of stroke varies according to both patient and procedural factors, the impact of genetic variants on stroke risk is not well understood. Therefore, we tested the hypothesis that specific genetic polymorphisms are associated with an increased risk of stroke after cardiac surgery. Methods— Patients undergoing cardiac surgery utilizing cardiopulmonary bypass surgery were studied. DNA was isolated from preoperative blood and analyzed for 26 different single-nucleotide polymorphisms. Multivariable logistic regression modeling was used to determine the association of clinical and genetic characteristics with stroke. Permutation analysis was used to adjust for multiple comparisons inherent in genetic association studies. Results— A total of 1635 patients experiencing 28 strokes (1.7%) were included in the final genetic model. The combination of the 2 minor alleles of C-reactive protein (CRP; 3′UTR 1846C/T) and interleukin-6 (IL-6; −174G/C) polymorphisms, occurring in 583 (35.7%) patients, was significantly associated with stroke (odds ratio, 3.3; 95% CI, 1.4 to 8.1; P=0.0023). In a multivariable logistic model adjusting for age, the CRP and IL-6 single-nucleotide polymorphism combination remained significantly associated with stroke (P=0.0020). Conclusions— We demonstrate that common genetic variants of CRP (3′UTR 1846C/T) and IL-6 (−174G/C) are significantly associated with the risk of stroke after cardiac surgery, suggesting a pivotal role of inflammation in post–cardiac surgery stroke.

Elucidation of veA-dependent genes associated with aflatoxin and sclerotial production in Aspergillus flavus by functional genomics

The aflatoxin-producing fungi, Aspergillus flavus and A. parasiticus, form structures called sclerotia that allow for survival under adverse conditions. Deletion of the veA gene in A. flavus and A. parasiticus blocks production of aflatoxin as well as sclerotial formation. We used microarray technology to identify genes differentially expressed in wild-type veA and veA mutant strains that could be involved in aflatoxin production and sclerotial development in A. flavus. The DNA microarray analysis revealed 684 genes whose expression changed significantly over time; 136 of these were differentially expressed between the two strains including 27 genes that demonstrated a significant difference in expression both between strains and over time. A group of 115 genes showed greater expression in the wild-type than in the veA mutant strain. We identified a subgroup of veA-dependent genes that exhibited time-dependent expression profiles similar to those of known aflatoxin biosynthetic genes or that were candidates for involvement in sclerotial production in the wild type.

Gene Profiling of Canine B-Cell Lymphoma Reveals Germinal Center and Postgerminal Center Subtypes with Different Survival Times, Modeling Human DLBCL

Diffuse large B-cell lymphoma (DLBCL) is the most common lymphoma subtype, and fewer than half of patients are cured with standard first-line therapy. To improve therapeutic options, better animal models that accurately mimic human DLBCL (hDLBCL) are needed. Canine DLBCL, one of the most common cancers in veterinary oncology, is morphologically similar to hDLBCL and is treated using similar chemotherapeutic protocols. With genomic technologies, it is now possible to molecularly evaluate dogs as a potential large-animal model for hDLBCL. We evaluated canine B-cell lymphomas (cBCL) using immunohistochemistry (IHC) and gene expression profiling. cBCL expression profiles were similar in many ways to hDLBCLs. For instance, a subset had increased expression of NF-κB pathway genes, mirroring human activated B-cell (ABC)-type DLBCL. Furthermore, immunoglobulin heavy chain ongoing mutation status, which is correlated with ABC/germinal center B-cell cell of origin in hDLBCL, separated cBCL into two groups with statistically different progression-free and overall survival times. In contrast with hDLBCL, cBCL rarely expressed BCL6 and MUM1/IRF4 by IHC. Collectively, these studies identify molecular similarities to hDLBCL that introduce pet dogs as a representative model of hDLBCL for future studies, including therapeutic clinical trials.

Comprehensive Transcriptome Profiling in Tomato Reveals a Role for Glycosyltransferase in Mi-Mediated Nematode Resistance

Root-knot nematode (RKN; Meloidogyne spp.) is a major crop pathogen worldwide. Effective resistance exists for a few plant species, including that conditioned by Mi in tomato (Solanum lycopersicum). We interrogated the root transcriptome of the resistant (Mi+) and susceptible (Mi–) cultivars ‘Motelle’ and ‘Moneymaker,’ respectively, during a time-course infection by the Mi-susceptible RKN species Meloidogyne incognita and the Mi-resistant species Meloidogyne hapla. In the absence of RKN infection, only a single significantly regulated gene, encoding a glycosyltransferase, was detected. However, RKN infection influenced the expression of broad suites of genes; more than half of the probes on the array identified differential gene regulation between infected and uninfected root tissue at some stage of RKN infection. We discovered 217 genes regulated during the time of RKN infection corresponding to establishment of feeding sites, and 58 genes that exhibited differential regulation in resistant roots compared to uninfected roots, including the glycosyltransferase. Using virus-induced gene silencing to silence the expression of this gene restored susceptibility to M. incognita in ‘Motelle,’ indicating that this gene is necessary for resistance to RKN. Collectively, our data provide a picture of global gene expression changes in roots during compatible and incompatible associations with RKN, and point to candidates for further investigation.

Characterization of canine osteosarcoma by array comparative genomic hybridization and RT-qPCR: Signatures of genomic imbalance in canine osteosarcoma parallel the human counterpart

Osteosarcoma (OS) is the most commonly diagnosed malignant bone tumor in humans and dogs, characterized in both species by extremely complex karyotypes exhibiting high frequencies of genomic imbalance. Evaluation of genomic signatures in human OS using array comparative genomic hybridization (aCGH) has assisted in uncovering genetic mechanisms that result in disease phenotype. Previous low‐resolution (10–20 Mb) aCGH analysis of canine OS identified a wide range of recurrent DNA copy number aberrations, indicating extensive genomic instability. In this study, we profiled 123 canine OS tumors by 1 Mb‐resolution aCGH to generate a dataset for direct comparison with current data for human OS, concluding that several high frequency aberrations in canine and human OS are orthologous. To ensure complete coverage of gene annotation, we identified the human refseq genes that map to these orthologous aberrant dog regions and found several candidate genes warranting evaluation for OS involvement. Specifically, subsequenct FISH and qRT‐PCR analysis of RUNX2, TUSC3, and PTEN indicated that expression levels correlated with genomic copy number status, showcasing RUNX2 as an OS associated gene and TUSC3 as a possible tumor suppressor candidate. Together these data demonstrate the ability of genomic comparative oncology to identify genetic abberations which may be important for OS progression. Large scale screening of genomic imbalance in canine OS further validates the use of the dog as a suitable model for human cancers, supporting the idea that dysregulation discovered in canine cancers will provide an avenue for complementary study in human counterparts.

Genomic architecture of adaptive color pattern divergence and convergence in Heliconius butterflies

Identifying the genetic changes driving adaptive variation in natural populations is key to understanding the origins of biodiversity. The mosaic of mimetic wing patterns in Heliconius butterflies makes an excellent system for exploring adaptive variation using next-generation sequencing. In this study, we use a combination of techniques to annotate the genomic interval modulating red color pattern variation, identify a narrow region responsible for adaptive divergence and convergence in Heliconius wing color patterns, and explore the evolutionary history of these adaptive alleles. We use whole genome resequencing from four hybrid zones between divergent color pattern races of Heliconius erato and two hybrid zones of the co-mimic Heliconius melpomene to examine genetic variation across 2.2 Mb of a partial reference sequence. In the intergenic region near optix, the gene previously shown to be responsible for the complex red pattern variation in Heliconius, population genetic analyses identify a shared 65-kb region of divergence that includes several sites perfectly associated with phenotype within each species. This region likely contains multiple cis-regulatory elements that control discrete expression domains of optix. The parallel signatures of genetic differentiation in H. erato and H. melpomene support a shared genetic architecture between the two distantly related co-mimics; however, phylogenetic analysis suggests mimetic patterns in each species evolved independently. Using a combination of next-generation sequencing analyses, we have refined our understanding of the genetic architecture of wing pattern variation in Heliconius and gained important insights into the evolution of novel adaptive phenotypes in natural populations.

Aspergillus flavus infection induces transcriptional and physical changes in developing maize kernels

Maize kernels are susceptible to infection by the opportunistic pathogen Aspergillus flavus. Infection results in reduction of grain quality and contamination of kernels with the highly carcinogenic mycotoxin, aflatoxin. To understanding host response to infection by the fungus, transcription of approximately 9000 maize genes were monitored during the host-pathogen interaction with a custom designed Affymetrix GeneChip® DNA array. More than 4000 maize genes were found differentially expressed at a FDR of 0.05. This included the up regulation of defense related genes and signaling pathways. Transcriptional changes also were observed in primary metabolism genes. Starch biosynthetic genes were down regulated during infection, while genes encoding maize hydrolytic enzymes, presumably involved in the degradation of host reserves, were up regulated. These data indicate that infection of the maize kernel by A. flavus induced metabolic changes in the kernel, including the production of a defense response, as well as a disruption in kernel development.