ASU Scholarship Showcase

Background: Meiotic recombination has traditionally been explained based on the structural requirement to stabilize homologous chromosome pairs to ensure their proper meiotic segregation. Competing hypotheses seek to explain the emerging findings of significant heterogeneity in recombination rates within and between genomes, but intraspecific comparisons of genome-wide recombination patterns are rare. The honey bee (Apis mellifera) exhibits the highest rate of genomic recombination among multicellular animals with about five cross-over events per chromatid.

Results: Here, we present a comparative analysis of recombination rates across eight genetic linkage maps of the honey bee genome to investigate which genomic sequence features are correlated with recombination rate and with its variation across the eight data sets, ranging in average marker spacing ranging from 1 Mbp to 120 kbp. Overall, we found that GC content explained best the variation in local recombination rate along chromosomes at the analyzed 100 kbp scale. In contrast, variation among the different maps was correlated to the abundance of microsatellites and several specific tri- and tetra-nucleotides.

Conclusions: The combined evidence from eight medium-scale recombination maps of the honey bee genome suggests that recombination rate variation in this highly recombining genome might be due to the DNA configuration instead of distinct sequence motifs. However, more fine-scale analyses are needed. The empirical basis of eight differing genetic maps allowed for robust conclusions about the correlates of the local recombination rates and enabled the study of the relation between DNA features and variability in local recombination rates, which is particularly relevant in the honey bee genome with its exceptionally high recombination rate.

Honeybee workers are essentially sterile female helpers that make up the majority of individuals in a colony. Workers display a marked change in physiology when they transition from in-nest tasks to foraging. Recent technological advances have made it possible to unravel the metabolic modifications associated with this transition. Previous studies have revealed extensive remodeling of brain, thorax, and hypopharyngeal gland biochemistry. However, data on changes in the abdomen is scarce. To narrow this gap we investigated the proteomic composition of abdominal tissue in the days typically preceding the onset of foraging in honeybee workers.

In order to get a broader representation of possible protein dynamics, we used workers of two genotypes with differences in the age at which they initiate foraging. This approach was combined with RNA interference-mediated downregulation of an insulin/insulin-like signaling component that is central to foraging behavior, the insulin receptor substrate (irs), and with measurements of glucose and lipid levels.
Our data provide new insight into the molecular underpinnings of phenotypic plasticity in the honeybee, invoke parallels with vertebrate metabolism, and support an integrated and irs-dependent association of carbohydrate and lipid metabolism with the transition from in-nest tasks to foraging.

Background: Omnivorous diets are high in arachidonic acid (AA) compared to vegetarian diets. Research shows that high intakes of AA promote changes in brain that can disturb mood. Omnivores who eat fish regularly increase their intakes of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), fats that oppose the negative effects of AA in vivo. In a recent cross-sectional study, omnivores reported significantly worse mood than vegetarians despite higher intakes of EPA and DHA. This study investigated the impact of restricting meat, fish, and poultry on mood.

Findings: Thirty-nine omnivores were randomly assigned to a control group consuming meat, fish, and poultry daily (OMN); a group consuming fish 3-4 times weekly but avoiding meat and poultry (FISH), or a vegetarian group avoiding meat, fish, and poultry (VEG). At baseline and after two weeks, participants completed a food frequency questionnaire, the Profile of Mood States questionnaire and the Depression Anxiety and Stress Scales. After the diet intervention, VEG participants reduced their EPA, DHA, and AA intakes, while FISH participants increased their EPA and DHA intakes. Mood scores were unchanged for OMN or FISH participants, but several mood scores for VEG participants improved significantly after two weeks.

Conclusions: Restricting meat, fish, and poultry improved some domains of short-term mood state in modern omnivores. To our knowledge, this is the first trial to examine the impact of restricting meat, fish, and poultry on mood state in omnivores.

Background: Obesity is a metabolic disease caused by environmental and genetic factors. However, the epigenetic mechanisms of obesity are incompletely understood. The aim of our study was to investigate the role of skeletal muscle DNA methylation in combination with transcriptomic changes in obesity.

Results: Muscle biopsies were obtained basally from lean (n = 12; BMI = 23.4 ± 0.7 kg/m[superscript 2]) and obese (n = 10; BMI = 32.9 ± 0.7 kg/m[superscript 2]) participants in combination with euglycemic-hyperinsulinemic clamps to assess insulin sensitivity. We performed reduced representation bisulfite sequencing (RRBS) next-generation methylation and microarray analyses on DNA and RNA isolated from vastus lateralis muscle biopsies. There were 13,130 differentially methylated cytosines (DMC; uncorrected P < 0.05) that were altered in the promoter and untranslated (5' and 3'UTR) regions in the obese versus lean analysis. Microarray analysis revealed 99 probes that were significantly (corrected P < 0.05) altered. Of these, 12 genes (encompassing 22 methylation sites) demonstrated a negative relationship between gene expression and DNA methylation. Specifically, sorbin and SH3 domain containing 3 (SORBS3) which codes for the adapter protein vinexin was significantly decreased in gene expression (fold change −1.9) and had nine DMCs that were significantly increased in methylation in obesity (methylation differences ranged from 5.0 to 24.4 %). Moreover, differentially methylated region (DMR) analysis identified a region in the 5'UTR (Chr.8:22,423,530–22,423,569) of SORBS3 that was increased in methylation by 11.2 % in the obese group. The negative relationship observed between DNA methylation and gene expression for SORBS3 was validated by a site-specific sequencing approach, pyrosequencing, and qRT-PCR. Additionally, we performed transcription factor binding analysis and identified a number of transcription factors whose binding to the differentially methylated sites or region may contribute to obesity.

Conclusions: These results demonstrate that obesity alters the epigenome through DNA methylation and highlights novel transcriptomic changes in SORBS3 in skeletal muscle.

We have previously hypothesized a biological pathway of activity-dependent synaptic plasticity proteins that addresses the dual genetic and environmental contributions to schizophrenia. Accordingly, variations in the immediate early gene EGR3, and its target ARC, should influence schizophrenia susceptibility. We used a pooled Next-Generation Sequencing approach to identify variants across these genes in U.S. populations of European (EU) and African (AA) descent. Three EGR3 and one ARC SNP were selected and genotyped for validation, and three SNPs were tested for association in a replication cohort. In the EU group of 386 schizophrenia cases and 150 controls EGR3 SNP rs1877670 and ARC SNP rs35900184 showed significant associations (p = 0.0078 and p = 0.0275, respectively). In the AA group of 185 cases and 50 controls, only the ARC SNP revealed significant association (p = 0.0448). The ARC SNP did not show association in the Han Chinese (CH) population. However, combining the EU, AA, and CH groups revealed a highly significant association of ARC SNP rs35900184 (p = 2.353 x 10^-7; OR [95% CI] = 1.54 [1.310–1.820]). These findings support previously reported associations between EGR3 and schizophrenia. Moreover, this is the first report associating an ARC SNP with schizophrenia and supports recent large-scale GWAS findings implicating the ARC complex in schizophrenia risk. These results support the need for further investigation of the proposed pathway of environmentally responsive, synaptic plasticity-related, schizophrenia genes.

Background: The physical health status of vegetarians has been extensively reported, but there is limited research regarding the mental health status of vegetarians, particularly with regard to mood. Vegetarian diets exclude fish, the major dietary source of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), critical regulators of brain cell structure and function. Omnivorous diets low in EPA and DHA are linked to impaired mood states in observational and experimental studies.

Methods: We examined associations between mood state and polyunsaturated fatty acid intake as a result of adherence to a vegetarian or omnivorous diet in a cross-sectional study of 138 healthy Seventh Day Adventist men and women residing in the Southwest. Participants completed a quantitative food frequency questionnaire, Depression Anxiety Stress Scale (DASS), and Profile of Mood States (POMS) questionnaires.

Results: Vegetarians (VEG:n = 60) reported significantly less negative emotion than omnivores (OMN:n = 78) as measured by both mean total DASS and POMS scores (8.32 ± 0.88 vs 17.51 ± 1.88, p = .000 and 0.10 ± 1.99 vs 15.33 ± 3.10, p = .007, respectively). VEG reported significantly lower mean intakes of EPA (p < .001), DHA (p < .001), as well as the omega-6 fatty acid, arachidonic acid (AA; p < .001), and reported higher mean intakes of shorter-chain α-linolenic acid (p < .001) and linoleic acid (p < .001) than OMN. Mean total DASS and POMS scores were positively related to mean intakes of EPA (p < 0.05), DHA (p < 0.05), and AA (p < 0.05), and inversely related to intakes of ALA (p < 0.05), and LA (p < 0.05), indicating that participants with low intakes of EPA, DHA, and AA and high intakes of ALA and LA had better mood.

Conclusions: The vegetarian diet profile does not appear to adversely affect mood despite low intake of long-chain omega-3 fatty acids.

Background: Immunosignaturing is a new peptide microarray based technology for profiling of humoral immune responses. Despite new challenges, immunosignaturing gives us the opportunity to explore new and fundamentally different research questions. In addition to classifying samples based on disease status, the complex patterns and latent factors underlying immunosignatures, which we attempt to model, may have a diverse range of applications.

Methods: We investigate the utility of a number of statistical methods to determine model performance and address challenges inherent in analyzing immunosignatures. Some of these methods include exploratory and confirmatory factor analyses, classical significance testing, structural equation and mixture modeling.

Results: We demonstrate an ability to classify samples based on disease status and show that immunosignaturing is a very promising technology for screening and presymptomatic screening of disease. In addition, we are able to model complex patterns and latent factors underlying immunosignatures. These latent factors may serve as biomarkers for disease and may play a key role in a bioinformatic method for antibody discovery.

Conclusion: Based on this research, we lay out an analytic framework illustrating how immunosignatures may be useful as a general method for screening and presymptomatic screening of disease as well as antibody discovery.

Background: Peanut consumption favorably influences satiety. This study examined the acute effect of peanut versus grain bar preloads on postmeal satiety and glycemia in healthy adults and the long-term effect of these meal preloads on body mass in healthy overweight adults.

Methods: In the acute crossover trial (n = 15; 28.4 ± 2.9 y; 23.1 ± 0.9 kg/m²), the preload (isoenergetic peanut or grain bar with water, or water alone) was followed after 60 min with ingestion of a standardized glycemic test meal. Satiety and blood glucose were assessed immediately prior to the preload and to the test meal, and for two hours postmeal at 30-min intervals. In the parallel-arm, randomized trial (n = 44; 40.5 ± 1.6 y, 31.8 ± 0.9 kg/m²), the peanut or grain bar preload was consumed one hour prior to the evening meal for eight weeks. Body mass was measured at 2-week intervals, and secondary endpoints included blood hemoglobin A1c and energy intake as assessed by 3-d diet records collected at pre-trial and trial weeks 1 and 8.

Results: Satiety was elevated in the postprandial period following grain bar ingestion in comparison to peanut or water ingestion (p = 0.001, repeated-measures ANOVA). Blood glucose was elevated one hour after ingestion of the grain bar as compared to the peanut or water treatments; yet, total glycemia did not vary between treatments in the two hour postprandial period. In the 8-week trial, body mass was reduced for the grain bar versus peanut groups after eight weeks (−1.3 ± 0.4 kg versus −0.2 ± 0.3 kg, p = 0.033, analysis of covariance). Energy intake was reduced by 458 kcal/d in the first week of the trial for the grain bar group as compared to the peanut group (p = 0.118). Hemoglobin A1c changed significantly between groups during the trial (−0.25 ± 0.07% and −0.18 ± 0.12% for the grain bar and peanut groups respectively, p = 0.001).

Conclusions: Compared to an isoenergetic peanut preload, consumption of a grain bar preload one hour prior to a standardized meal significantly raised postmeal satiety. Moreover, consumption of the grain bar prior to the evening meal was associated with significant weight loss over time suggesting that glycemic carbohydrate ingestion prior to meals may be a weight management strategy.

Background: Glioblastoma is the most aggressive primary central nervous tumor and carries a very poor prognosis. Invasion precludes effective treatment and virtually assures tumor recurrence. In the current study, we applied analytical and bioinformatics approaches to identify a set of microRNAs (miRs) from several different human glioblastoma cell lines that exhibit significant differential expression between migratory (edge) and migration-restricted (core) cell populations. The hypothesis of the study is that differential expression of miRs provides an epigenetic mechanism to drive cell migration and invasion.

Results: Our research data comprise gene expression values for a set of 805 human miRs collected from matched pairs of migratory and migration-restricted cell populations from seven different glioblastoma cell lines. We identified 62 down-regulated and 2 up-regulated miRs that exhibit significant differential expression in the migratory (edge) cell population compared to matched migration-restricted (core) cells. We then conducted target prediction and pathway enrichment analysis with these miRs to investigate potential associated gene and pathway targets. Several miRs in the list appear to directly target apoptosis related genes. The analysis identifies a set of genes that are predicted by 3 different algorithms, further emphasizing the potential validity of these miRs to promote glioblastoma.

Conclusions: The results of this study identify a set of miRs with potential for decreased expression in invasive glioblastoma cells. The verification of these miRs and their associated targeted proteins provides new insights for further investigation into therapeutic interventions. The methodological approaches employed here could be applied to the study of other diseases to provide biomedical researchers and clinicians with increased opportunities for therapeutic interventions.

Background: The discovery of genetic associations is an important factor in the understanding of human illness to derive disease pathways. Identifying multiple interacting genetic mutations associated with disease remains challenging in studying the etiology of complex diseases. And although recently new single nucleotide polymorphisms (SNPs) at genes implicated in immune response, cholesterol/lipid metabolism, and cell membrane processes have been confirmed by genome-wide association studies (GWAS) to be associated with late-onset Alzheimer's disease (LOAD), a percentage of AD heritability continues to be unexplained. We try to find other genetic variants that may influence LOAD risk utilizing data mining methods.

Methods: Two different approaches were devised to select SNPs associated with LOAD in a publicly available GWAS data set consisting of three cohorts. In both approaches, single-locus analysis (logistic regression) was conducted to filter the data with a less conservative p-value than the Bonferroni threshold; this resulted in a subset of SNPs used next in multi-locus analysis (random forest (RF)). In the second approach, we took into account prior biological knowledge, and performed sample stratification and linkage disequilibrium (LD) in addition to logistic regression analysis to preselect loci to input into the RF classifier construction step.

Results: The first approach gave 199 SNPs mostly associated with genes in calcium signaling, cell adhesion, endocytosis, immune response, and synaptic function. These SNPs together with APOE and GAB2 SNPs formed a predictive subset for LOAD status with an average error of 9.8% using 10-fold cross validation (CV) in RF modeling. Nineteen variants in LD with ST5, TRPC1, ATG10, ANO3, NDUFA12, and NISCH respectively, genes linked directly or indirectly with neurobiology, were identified with the second approach. These variants were part of a model that included APOE and GAB2 SNPs to predict LOAD risk which produced a 10-fold CV average error of 17.5% in the classification modeling.

Conclusions: With the two proposed approaches, we identified a large subset of SNPs in genes mostly clustered around specific pathways/functions and a smaller set of SNPs, within or in proximity to five genes not previously reported, that may be relevant for the prediction/understanding of AD.