Using phenome-wide association studies and the SF-12 quality of life metric to identify profound consequences of adverse childhood experiences on adult mental and physical health in a Northern Nevadan population.

In this research, we examine and identify the implications of Adverse Childhood Experiences (ACEs) on a range of health outcomes, with particular focus on a number of mental health disorders. Many previous studies observed that traumatic childhood events are linked to long-term adult diseases using the standard Adverse Childhood Experience Questionnaire. The study cohort was derived from the Healthy Nevada Project, a volunteer-based population health study in which each adult participant is invited to take a retrospective questionnaire that includes the Adverse Childhood Experience Questionnaire, the 12-item Short Form Survey measuring quality of life, and self-reported incidence of nine mental disorders. Using participant's cross-referenced electronic health records, a phenome-wide association analysis of 1,703 phenotypes and the incidence of ACEs examined links between traumatic events in childhood and adult disease. These analyses showed that many mental disorders were significantly associated with ACEs in a dose-response manner. Similarly, a dose response between ACEs and obesity, chronic pain, migraine, and other physical phenotypes was identified. An examination of the prevalence of self-reported mental disorders and incidence of ACEs showed a positive relationship. Furthermore, participants with less adverse childhood events experienced a higher quality of life, both physically and mentally. The whole-phenotype approach confirms that ACEs are linked with many negative adult physical and mental health outcomes. With the nationwide prevalence of ACEs as high as 67%, these findings suggest a need for new public health resources: ACE-specific interventions and early childhood screenings.

The Impact of ACEs on BMI: An Investigation of the Genotype-Environment Effects of BMI.

Adverse Childhood Experiences are stressful and traumatic events occurring before the age of eighteen shown to cause mental and physical health problems, including increased risk of obesity. Obesity remains an ongoing national challenge with no predicted solution. We examine a subset of the Healthy Nevada Project, focusing on a multi-ethnic cohort of 15,886 sequenced participants with recalled adverse childhood events, to study how ACEs and their genotype-environment interactions affect BMI. Specifically, the Healthy Nevada Project participants sequenced by the Helix Exome+ platform were cross-referenced to their electronic medical records and social health determinants questionnaire to identify: 1) the effect of ACEs on BMI in the absence of genetics; 2) the effect of genotype-environment interactions on BMI; 3) how these gene-environment interactions differ from standard genetic associations of BMI. The study found very strong significant associations between the number of adverse childhood experiences and adult obesity. Additionally, we identified fifty-five common and rare variants that exhibited gene-interaction effects including three variants in the CAMK1D gene and four variants in LHPP; both genes are linked to schizophrenia. Surprisingly, none of the variants identified with interactive effects were in canonical obesity-related genes. Here we show the delicate balance between genes and environment, and how the two strongly influence each other.

Genome-Wide Identification of Rare and Common Variants Driving Triglyceride Levels in a Nevada Population.

Clinical conditions correlated with elevated triglyceride levels are well-known: coronary heart disease, hypertension, and diabetes. Underlying genetic and phenotypic mechanisms are not fully understood, partially due to lack of coordinated genotypic-phenotypic data. Here we use a subset of the Healthy Nevada Project, a population of 9,183 sequenced participants with longitudinal electronic health records to examine consequences of altered triglyceride levels. Specifically, Healthy Nevada Project participants sequenced by the Helix Exome+ platform were cross-referenced to their electronic medical records to identify: (1) rare and common single-variant genome-wide associations; (2) gene-based associations using a Sequence Kernel Association Test; (3) phenome-wide associations with triglyceride levels; and (4) pleiotropic variants linked to triglyceride levels. The study identified 549 significant single-variant associations (p < 8.75 × 10-9), many in chromosome 11's triglyceride hotspot: ZPR1, BUD13, APOC3, APOA5. A well-known protective loss-of-function variant in APOC3 (R19X) was associated with a 51% decrease in triglyceride levels in the cohort. Sixteen gene-based triglyceride associations were identified; six of these genes surprisingly did not include a single variant with significant associations. Results at the variant and gene level were validated with the UK Biobank. The combination of a single-variant genome-wide association, a gene-based association method, and phenome wide-association studies identified rare and common variants, genes, and phenotypes associated with elevated triglyceride levels, some of which may have been overlooked with standard approaches.

Characterization of novel pollen-expressed transcripts reveals their potential roles in pollen heat stress response in Arabidopsis thaliana.

KEY MESSAGE: Arabidopsis pollen transcriptome analysis revealed new intergenic transcripts of unknown function, many of which are long non-coding RNAs, that may function in pollen-specific processes, including the heat stress response. The male gametophyte is the most heat sensitive of all plant tissues. In recent years, long noncoding RNAs (lncRNAs) have emerged as important components of cellular regulatory networks involved in most biological processes, including response to stress. While examining RNAseq datasets of developing and germinating Arabidopsis thaliana pollen exposed to heat stress (HS), we identified 66 novel and 246 recently annotated intergenic expressed loci (XLOCs) of unknown function, with the majority encoding lncRNAs. Comparison with HS in cauline leaves and other RNAseq experiments indicated that 74% of the 312 XLOCs are pollen-specific, and at least 42% are HS-responsive. Phylogenetic analysis revealed that 96% of the genes evolved recently in Brassicaceae. We found that 50 genes are putative targets of microRNAs and that 30% of the XLOCs contain small open reading frames (ORFs) with homology to protein sequences. Finally, RNAseq of ribosome-protected RNA fragments together with predictions of periodic footprint of the ribosome P-sites indicated that 23 of these ORFs are likely to be translated. Our findings indicate that many of the 312 unknown genes might be functional and play a significant role in pollen biology, including the HS response.

Drought tolerance of the grapevine, Vitis champinii cv. Ramsey, is associated with higher photosynthesis and greater transcriptomic responsiveness of abscisic acid biosynthesis and signaling.

BACKGROUND: Grapevine is an economically important crop for which yield and berry quality is strongly affected by climate change. Large variations in drought tolerance exist across Vitis species. Some of these species are used as rootstock to enhance abiotic and biotic stress tolerance. In this study, we investigated the physiological and transcriptomic responses to water deficit of four different genotypes that differ in drought tolerance: Ramsey (Vitis champinii), Riparia Gloire (Vitis riparia), Cabernet Sauvignon (Vitis vinifera), and SC2 (Vitis vinifera x Vitis girdiana). RESULTS: Ramsey was particularly more drought tolerant than the other three genotypes. Ramsey maintained a higher stomatal conductance and photosynthesis at equivalent levels of moderate water deficit. We identified specific and common transcriptomic responses shared among the four different Vitis species using RNA sequencing analysis. A weighted gene co-expression analysis identified a water deficit core gene set with the ABA biosynthesis and signaling genes, NCED3, RD29B and ABI1 as potential hub genes. The transcript abundance of many abscisic acid metabolism and signaling genes was strongly increased by water deficit along with genes associated with lipid metabolism, galactinol synthases and MIP family proteins. This response occurred at smaller water deficits in Ramsey and with higher transcript abundance than the other genotypes. A number of aquaporin genes displayed differential and unique responses to water deficit in Ramsey leaves. Genes involved in cysteine biosynthesis and metabolism were constitutively higher in the roots of Ramsey; thus, linking the gene expression of a known factor that influences ABA biosynthesis to this genotype's increased NCED3 transcript abundance. CONCLUSION: The drought tolerant Ramsey maintained higher photosynthesis at equivalent water deficit than the three other grapevine genotypes. Ramsey was more responsive to water deficit; its transcriptome responded at smaller water deficits, whereas the other genotypes did not respond until more severe water deficits were reached. There was a common core gene network responding to water deficit for all genotypes that included ABA metabolism and signaling. The gene clusters and sub-networks identified in this work represent interesting gene lists to explore and to better understand drought tolerance molecular mechanisms.

Genome-wide rare variant analysis for thousands of phenotypes in over 70,000 exomes from two cohorts.

Understanding the impact of rare variants is essential to understanding human health. We analyze rare (MAF < 0.1%) variants against 4264 phenotypes in 49,960 exome-sequenced individuals from the UK Biobank and 1934 phenotypes (1821 overlapping with UK Biobank) in 21,866 members of the Healthy Nevada Project (HNP) cohort who underwent Exome + sequencing at Helix. After using our rare-variant-tailored methodology to reduce test statistic inflation, we identify 64 statistically significant gene-based associations in our meta-analysis of the two cohorts and 37 for phenotypes available in only one cohort. Singletons make significant contributions to our results, and the vast majority of the associations could not have been identified with a genotyping chip. Our results are available for interactive browsing in a webapp (https://ukb.research.helix.com). This comprehensive analysis illustrates the biological value of large, deeply phenotyped cohorts of unselected populations coupled with NGS data.

A Comprehensive Genome-Wide and Phenome-Wide Examination of BMI and Obesity in a Northern Nevadan Cohort.

The aggregation of Electronic Health Records (EHR) and personalized genetics leads to powerful discoveries relevant to population health. Here we perform genome-wide association studies (GWAS) and accompanying phenome-wide association studies (PheWAS) to validate phenotype-genotype associations of BMI, and to a greater extent, severe Class 2 obesity, using comprehensive diagnostic and clinical data from the EHR database of our cohort. Three GWASs of 500,000 variants on the Illumina platform of 6,645 Healthy Nevada participants identified several published and novel variants that affect BMI and obesity. Each GWAS was followed with two independent PheWASs to examine associations between extensive phenotypes (incidence of diagnoses, condition, or disease), significant SNPs, BMI, and incidence of extreme obesity. The first GWAS examines associations with BMI in a cohort with no type 2 diabetics, focusing exclusively on BMI. The second GWAS examines associations with BMI in a cohort that includes type 2 diabetics. In the second GWAS, type 2 diabetes is a comorbidity, and thus becomes a covariate in the statistical model. The intersection of significant variants of these two studies is surprising. The third GWAS is a case vs. control study, with cases defined as extremely obese (Class 2 or 3 obesity), and controls defined as participants with BMI between 18.5 and 25. This last GWAS identifies strong associations with extreme obesity, including established variants in the FTO and NEGR1 genes, as well as loci not yet linked to obesity. The PheWASs validate published associations between BMI and extreme obesity and incidence of specific diagnoses and conditions, yet also highlight novel links. This study emphasizes the importance of our extensive longitudinal EHR database to validate known associations and identify putative novel links with BMI and obesity.

GWAS and PheWAS of red blood cell components in a Northern Nevadan cohort.

In this study, we perform a full genome-wide association study (GWAS) to identify statistically significantly associated single nucleotide polymorphisms (SNPs) with three red blood cell (RBC) components and follow it with two independent PheWASs to examine associations between phenotypic data (case-control status of diagnoses or disease), significant SNPs, and RBC component levels. We first identified associations between the three RBC components: mean platelet volume (MPV), mean corpuscular volume (MCV), and platelet counts (PC), and the genotypes of approximately 500,000 SNPs on the Illumina Infimum DNA Human OmniExpress-24 BeadChip using a single cohort of 4,673 Northern Nevadans. Twenty-one SNPs in five major genomic regions were found to be statistically significantly associated with MPV, two regions with MCV, and one region with PC, with p<5x10-8. Twenty-nine SNPs and nine chromosomal regions were identified in 30 previous GWASs, with effect sizes of similar magnitude and direction as found in our cohort. The two strongest associations were SNP rs1354034 with MPV (p = 2.4x10-13) and rs855791 with MCV (p = 5.2x10-12). We then examined possible associations between these significant SNPs and incidence of 1,488 phenotype groups mapped from International Classification of Disease version 9 and 10 (ICD9 and ICD10) codes collected in the extensive electronic health record (EHR) database associated with Healthy Nevada Project consented participants. Further leveraging data collected in the EHR, we performed an additional PheWAS to identify associations between continuous red blood cell (RBC) component measures and incidence of specific diagnoses. The first PheWAS illuminated whether SNPs associated with RBC components in our cohort were linked with other hematologic phenotypic diagnoses or diagnoses of other nature. Although no SNPs from our GWAS were identified as strongly associated to other phenotypic components, a number of associations were identified with p-values ranging between 1x10-3 and 1x10-4 with traits such as respiratory failure, sleep disorders, hypoglycemia, hyperglyceridemia, GERD and IBS. The second PheWAS examined possible phenotypic predictors of abnormal RBC component measures: a number of hematologic phenotypes such as thrombocytopenia, anemias, hemoglobinopathies and pancytopenia were found to be strongly associated to RBC component measures; additional phenotypes such as (morbid) obesity, malaise and fatigue, alcoholism, and cirrhosis were also identified to be possible predictors of RBC component measures.

Single-nucleotide polymorphisms in a cohort of significantly obese women without cardiometabolic diseases.

BACKGROUND/OBJECTIVES: Obesity is an important risk factor for the development of diseases such as diabetes mellitus, hypertension, and dyslipidemia; however, a small number of individuals with long-standing obesity do not present with these cardiometabolic diseases. Such individuals are referred to as metabolically healthy obese (MHO) and potentially represent a subgroup of the general population with a protective genetic predisposition to obesity-related diseases. We hypothesized that individuals who were metabolically healthy, but significantly obese (BMI ≥ 35 kg/m2) would represent a highly homogenous subgroup, with which to investigate potential genetic associations to obesity. We further hypothesized that such a cohort may lend itself well to investigate potential genotypes that are protective with respect to the development of cardiometabolic disease. SUBJECTS/METHODS: In the present study, we implemented this novel selection strategy by screening 892 individuals diagnosed as Class 2 or Class 3 obese and identified 38 who presented no manifestations of cardiometabolic disease. We then assessed these subjects for single-nucleotide polymorphisms (SNPs) that associated with this phenotype. RESULTS: Our analysis identified 89 SNPs that reach statistical significance (p < 1 × 10-5), some of which are associated with genes of biological pathways that influences dietary behavior; others are associated with genes previously linked to obesity and cardiometabolic disease as well as neuroimmune disease. This study, to the best of our knowledge, represents the first genetic screening of a cardiometabolically healthy, but significantly obese population.

Evaluation of four clinical laboratory parameters for the diagnosis of myalgic encephalomyelitis.

BACKGROUND: Myalgic encephalomyelitis (ME) is a complex and debilitating disease that often initially presents with flu-like symptoms, accompanied by incapacitating fatigue. Currently, there are no objective biomarkers or laboratory tests that can be used to unequivocally diagnosis ME; therefore, a diagnosis is made when a patient meets series of a costly and subjective inclusion and exclusion criteria. The purpose of the present study was to evaluate the utility of four clinical parameters in diagnosing ME. METHODS: In the present study, we utilized logistic regression and classification and regression tree analysis to conduct a retrospective investigation of four clinical laboratory in 140 ME cases and 140 healthy controls. RESULTS: Correlations between the covariates ranged between [- 0.26, 0.61]. The best model included the serum levels of the soluble form of CD14 (sCD14), serum levels of prostaglandin E2 (PGE2), and serum levels of interleukin 8, with coefficients 0.002, 0.249, and 0.005, respectively, and p-values of 3 × 10-7, 1 × 10-5, and 3 × 10-3, respectively. CONCLUSIONS: Our findings show that these parameters may help physicians in their diagnosis of ME and may additionally shed light on the pathophysiology of this disease.

A comparison of heat-stress transcriptome changes between wild-type Arabidopsis pollen and a heat-sensitive mutant harboring a knockout of cyclic nucleotide-gated cation channel 16 (cngc16).

BACKGROUND: In flowering plants, the male gametophyte (pollen) is one of the most vulnerable cells to temperature stress. In Arabidopsis thaliana, a pollen-specific Cyclic Nucleotide-Gated cation Channel 16 (cngc16), is required for plant reproduction under temperature-stress conditions. Plants harboring a cncg16 knockout are nearly sterile under conditions of hot days and cold nights. To understand the underlying cause, RNA-Seq was used to compare the pollen transcriptomes of wild type (WT) and cngc16 under normal and heat stress (HS) conditions. RESULTS: Here we show that a heat-stress response (HSR) in WT pollen resulted in 2102 statistically significant transcriptome changes (≥ 2-fold changes with adjusted p-value ≤0.01), representing approximately 15% of 14,226 quantified transcripts. Of these changes, 89 corresponded to transcription factors, with 27 showing a preferential expression in pollen over seedling tissues. In contrast to WT, cngc16 pollen showed 1.9-fold more HS-dependent changes (3936 total, with 2776 differences between WT and cngc16). In a quantitative direct comparison between WT and cngc16 transcriptomes, the number of statistically significant differences increased from 21 pre-existing differences under normal conditions to 192 differences under HS. Of the 20 HS-dependent changes in WT that were most different in cngc16, half corresponded to genes encoding proteins predicted to impact cell wall features or membrane dynamics. CONCLUSIONS: Results here define an extensive HS-dependent reprogramming of approximately 15% of the WT pollen transcriptome, and identify at least 27 transcription factor changes that could provide unique contributions to a pollen HSR. The number of statistically significant transcriptome differences between WT and cngc16 increased by more than 9-fold under HS, with most of the largest magnitude changes having the potential to specifically impact cell walls or membrane dynamics, and thereby potentiate cngc16 pollen to be hypersensitive to HS. However, HS-hypersensitivity could also be caused by the extensive number of differences throughout the transcriptome having a cumulative effect on multiple cellular pathways required for tip growth and fertilization. Regardless, results here support a model in which a functional HS-dependent reprogramming of the pollen transcriptome requires a specific calcium-permeable Cyclic Nucleotide-Gated cation Channel, CNGC16.

Humoral Immunity Profiling of Subjects with Myalgic Encephalomyelitis Using a Random Peptide Microarray Differentiates Cases from Controls with High Specificity and Sensitivity.

Myalgic encephalomyelitis (ME) is a complex, heterogeneous illness of unknown etiology. The search for biomarkers that can delineate cases from controls is one of the most active areas of ME research; however, little progress has been made in achieving this goal. In contrast to identifying biomarkers that are directly involved in the pathological process, an immunosignature identifies antibodies raised to proteins expressed during, and potentially involved in, the pathological process. Although these proteins might be unknown, it is possible to detect antibodies that react to these proteins using random peptide arrays. In the present study, we probe a custom 125,000 random 12-mer peptide microarray with sera from 21 ME cases and 21 controls from the USA and Europe and used these data to develop a diagnostic signature. We further used these peptide sequences to potentially uncover the naturally occurring candidate antigens to which these antibodies may specifically react with in vivo. Our analysis revealed a subset of 25 peptides that distinguished cases and controls with high specificity and sensitivity. Additionally, Basic Local Alignment Search Tool (BLAST) searches suggest that these peptides primarily represent human self-antigens and endogenous retroviral sequences and, to a minor extent, viral and bacterial pathogens.

The common transcriptional subnetworks of the grape berry skin in the late stages of ripening.

BACKGROUND: Wine grapes are important economically in many countries around the world. Defining the optimum time for grape harvest is a major challenge to the grower and winemaker. Berry skins are an important source of flavor, color and other quality traits in the ripening stage. Senescent-like processes such as chloroplast disorganization and cell death characterize the late ripening stage. RESULTS: To better understand the molecular and physiological processes involved in the late stages of berry ripening, RNA-seq analysis of the skins of seven wine grape cultivars (Cabernet Franc, Cabernet Sauvignon, Merlot, Pinot Noir, Chardonnay, Sauvignon Blanc and Semillon) was performed. RNA-seq analysis identified approximately 2000 common differentially expressed genes for all seven cultivars across four different berry sugar levels (20 to 26 °Brix). Network analyses, both a posteriori (standard) and a priori (gene co-expression network analysis), were used to elucidate transcriptional subnetworks and hub genes associated with traits in the berry skins of the late stages of berry ripening. These independent approaches revealed genes involved in photosynthesis, catabolism, and nucleotide metabolism. The transcript abundance of most photosynthetic genes declined with increasing sugar levels in the berries. The transcript abundance of other processes increased such as nucleic acid metabolism, chromosome organization and lipid catabolism. Weighted gene co-expression network analysis (WGCNA) identified 64 gene modules that were organized into 12 subnetworks of three modules or more and six higher order gene subnetworks. Some gene subnetworks were highly correlated with sugar levels and some subnetworks were highly enriched in the chloroplast and nucleus. The petal R package was utilized independently to construct a true small-world and scale-free complex gene co-expression network model. A subnetwork of 216 genes with the highest connectivity was elucidated, consistent with the module results from WGCNA. Hub genes in these subnetworks were identified including numerous members of the core circadian clock, RNA splicing, proteolysis and chromosome organization. An integrated model was constructed linking light sensing with alternative splicing, chromosome remodeling and the circadian clock. CONCLUSIONS: A common set of differentially expressed genes and gene subnetworks from seven different cultivars were examined in the skin of the late stages of grapevine berry ripening. A densely connected gene subnetwork was elucidated involving a complex interaction of berry senescent processes (autophagy), catabolism, the circadian clock, RNA splicing, proteolysis and epigenetic regulation. Hypotheses were induced from these data sets involving sugar accumulation, light, autophagy, epigenetic regulation, and fruit development. This work provides a better understanding of berry development and the transcriptional processes involved in the late stages of ripening.

Sporobolus stapfianus: Insights into desiccation tolerance in the resurrection grasses from linking transcriptomics to metabolomics.

BACKGROUND: Understanding the response of resurrection angiosperms to dehydration and rehydration is critical for deciphering the mechanisms of how plants cope with the rigors of water loss from their vegetative tissues. We have focused our studies on the C4 resurrection grass, Sporobolus stapfianus Gandoger, as a member of a group of important forage grasses. METHODS: We have combined non-targeted metabolomics with transcriptomics, via a NimbleGen array platform, to develop an understanding of how gene expression and metabolite profiles can be linked to generate a more detailed mechanistic appreciation of the cellular response to both desiccation and rehydration. RESULTS: The rehydration transcriptome and metabolome are primarily geared towards the rapid return of photosynthesis, energy metabolism, protein turnover, and protein synthesis during the rehydration phase. However, there are some metabolites associated with ROS protection that remain elevated during rehydration, most notably the tocopherols. The analysis of the dehydration transcriptome reveals a strong concordance between transcript abundance and the associated metabolite abundance reported earlier, but only in responses that are directly related to cellular protection during dehydration: carbohydrate metabolism and redox homeostasis. The transcriptome response also provides strong support for the involvement of cellular protection processes as exemplified by the increases in the abundance of transcripts encoding late embryogenesis abundant (LEA) proteins, anti-oxidant enzymes, early light-induced proteins (ELIP) proteins, and cell-wall modification enzymes. There is little concordance between transcript and metabolite abundance for processes such as amino acid metabolism that do not appear to contribute directly to cellular protection, but are nonetheless important for the desiccation tolerant phenotype of S. stapfianus. CONCLUSIONS: The transcriptomes of both dehydration and rehydration offer insight into the complexity of the regulation of responses to these processes that involve complex signaling pathways and associated transcription factors. ABA appears to be important in the control of gene expression in both the latter stages of the dehydration and the early stages of rehydration. These findings add to the growing body of information detailing how plants tolerate and survive the severe cellular perturbations of dehydration, desiccation, and rehydration.

Transcriptional Analysis of Blood Lymphocytes and Skin Fibroblasts, Keratinocytes, and Endothelial Cells as a Potential Biomarker for Alzheimer's Disease.

Alzheimer's disease (AD) is a devastating and progressive form of dementia that is typically associated with a build-up of amyloid-ß plaques and hyperphosphorylated and misfolded tau protein in the brain. Presently, there is no single test that confirms AD; therefore, a definitive diagnosis is only made after a comprehensive medical evaluation, which includes medical history, cognitive tests, and a neurological examination and/or brain imaging. Additionally, the protracted prodromal phase of the disease makes selection of control subjects for clinical trials challenging. In this study we have utilized a gene-expression array to screen blood and skin punch biopsy (fibroblasts, keratinocytes, and endothelial cells) for transcriptional differences that may lead to a greater understanding of AD as well as identify potential biomarkers. Our analysis identified 129 differentially expressed genes from blood of dementia cases when compared to healthy individuals, and four differentially expressed punch biopsy genes between AD subjects and controls. Additionally, we identified a set of genes in both tissue compartments that showed transcriptional variation in AD but were largely stable in controls. The translational products of these variable genes are involved in the maintenance of the Golgi structure, regulation of lipid metabolism, DNA repair, and chromatin remodeling. Our analysis potentially identifies specific genes in both tissue compartments that may ultimately lead to useful biomarkers and may provide new insight into the pathophysiology of AD.

petal: Co-expression network modelling in R.

BACKGROUND: Networks provide effective models to study complex biological systems, such as gene and protein interaction networks. With the advent of new sequencing technologies, many life scientists are grasping for user-friendly methods and tools to examine biological components at the whole-systems level. Gene co-expression network analysis approaches are frequently used to successfully associate genes with biological processes and demonstrate great potential to gain further insights into the functionality of genes, thus becoming a standard approach in Systems Biology. Here the objective is to construct biologically meaningful and statistically strong co-expression networks, the identification of research dependent subnetworks, and the presentation of self-contained results. RESULTS: We introduce petal, a novel approach to generate gene co-expression network models based on experimental gene expression measures. petal focuses on statistical, mathematical, and biological characteristics of both, input data and output network models. Often over-looked issues of current co-expression analysis tools include the assumption of data normality, which is seldom the case for hight-throughput expression data obtained from RNA-seq technologies. petal does not assume data normality, making it a statistically appropriate method for RNA-seq data. Also, network models are rarely tested for their known typical architecture: scale-free and small-world. petal explicitly constructs networks based on both these characteristics, thereby generating biologically meaningful models. Furthermore, many network analysis tools require a number of user-defined input variables, these often require tuning and/or an understanding of the underlying algorithm; petal requires no user input other than experimental data. This allows for reproducible results, and simplifies the use of petal. Lastly, this approach is specifically designed for very large high-throughput datasets; this way, petal's network models represent as much of the entire system as possible to provide a whole-system approach. CONCLUSION: petal is a novel tool for generating co-expression network models of whole-genomics experiments. It is implemented in R and available as a library. Its application to several whole-genome experiments has generated novel meaningful results and has lead the way to new testing hypothesizes for further biological investigation.

Transcriptomic network analyses of leaf dehydration responses identify highly connected ABA and ethylene signaling hubs in three grapevine species differing in drought tolerance.

BACKGROUND: Grapevine is a major food crop that is affected by global climate change. Consistent with field studies, dehydration assays of grapevine leaves can reveal valuable information of the plant's response at physiological, transcript, and protein levels. There are well-known differences in grapevine rootstocks responses to dehydration. We used time-series transcriptomic approaches combined with network analyses to elucidate and identify important physiological processes and network hubs that responded to dehydration in three different grapevine species differing in their drought tolerance. RESULTS: Transcriptomic analyses of the leaves of Cabernet Sauvignon, Riparia Gloire, and Ramsey were evaluated at different times during a 24-h controlled dehydration. Analysis of variance (ANOVA) revealed that approximately 11,000 transcripts changed significantly with respect to the genotype x treatment interaction term and approximately 6000 transcripts changed significantly according to the genotype x treatment x time interaction term indicating massive differential changes in gene expression over time. Standard analyses determined substantial effects on the transcript abundance of genes involved in the metabolism and signaling of two known plant stress hormones, abscisic acid (ABA) and ethylene. ABA and ethylene signaling maps were constructed and revealed specific changes in transcript abundance that were associated with the known drought tolerance of the genotypes including genes such as VviABI5, VviABF2, VviACS2, and VviWRKY22. Weighted-gene coexpression network analysis (WGCNA) confirmed these results. In particular, WGCNA identified 30 different modules, some of which had highly enriched gene ontology (GO) categories for photosynthesis, phenylpropanoid metabolism, ABA and ethylene signaling. The ABA signaling transcription factors, VviABI5 and VviABF2, were highly connected hubs in two modules, one being enriched in gaseous transport and the other in ethylene signaling. VviABI5 was distinctly correlated with an early response and high expression for the drought tolerant Ramsey and with little response from the drought sensitive Riparia Gloire. These ABA signaling transcription factors were highly connected to VviSnRK1 and other gene hubs associated with sugar, ethylene and ABA signaling. CONCLUSION: A leaf dehydration assay provided transcriptomic evidence for differential leaf responses to dehydration between genotypes differing in their drought tolerance. WGCNA proved to be a powerful network analysis approach; it identified 30 distinct modules (networks) with highly enriched GO categories and enabled the identification of gene hubs in these modules. Some of these genes were highly connected hubs in both the ABA and ethylene signaling pathways, supporting the hypothesis that there is substantial crosstalk between the two hormone pathways. This study identifies solid gene candidates for future investigations of drought tolerance in grapevine.

Abscisic acid transcriptomic signaling varies with grapevine organ.

BACKGROUND: Abscisic acid (ABA) regulates various developmental processes and stress responses over both short (i.e. hours or days) and longer (i.e. months or seasons) time frames. To elucidate the transcriptional regulation of early responses of grapevine (Vitis vinifera) responding to ABA, different organs of grape (berries, shoot tips, leaves, roots and cell cultures) were treated with 10 µM (S)-(+)-ABA for 2 h. NimbleGen whole genome microarrays of Vitis vinifera were used to determine the effects of ABA on organ-specific mRNA expression patterns. RESULTS: Transcriptomic analysis revealed 839 genes whose transcript abundances varied significantly in a specific organ in response to ABA treatment. No single gene exhibited the same changes in transcript abundance across all organs in response to ABA. The biochemical pathways affected by ABA were identified using the Cytoscape program with the BiNGO plug-in software. The results indicated that these 839 genes were involved in several biological processes such as flavonoid metabolism, response to reactive oxygen species, response to light, and response to temperature stimulus. ABA affected ion and water transporters, particularly in the root. The protein amino acid phosphorylation process was significantly overrepresented in shoot tips and roots treated with ABA. ABA affected mRNA abundance of genes (CYP707As, UGTs, and PP2Cs) associated with ABA degradation, conjugation, and the ABA signaling pathway. ABA also significantly affected the expression of several transcription factors (e.g. AP2/ERF, MYC/MYB, and bZIP/AREB). The greatest number of significantly differentially expressed genes was observed in the roots followed by cell cultures, leaves, berries, and shoot tips, respectively. Each organ had a unique set of gene responses to ABA. CONCLUSIONS: This study examined the short-term effects of ABA on different organs of grapevine. The responses of each organ were unique indicating that ABA signaling varies with the organ. Understanding the ABA responses in an organ-specific manner is crucial to fully understand hormone action and plant responses to water deficit.

Previously Unidentified Single Nucleotide Polymorphisms in HIV/AIDS Cases Associate with Clinical Parameters and Disease Progression.

The genetic background of an individual plays an important role in the progression of HIV infection to AIDS. Identifying previously unknown or uncharacterized single nucleotide polymorphisms (SNPs) that associate with disease progression may reveal important therapeutic targets and provide a greater understanding of disease pathogenesis. In the present study, we employed ultra-high multiplex PCR on an Ion Torrent next-generation sequencing platform to sequence 23 innate immune genes from 94 individuals with HIV/AIDS. This data was used to identify potential associations of SNPs with clinical parameters and disease progression. SNPs that associated with an increased viral load were identified in the genes for the interleukin 15 receptor (IL15RA), toll-like receptor 7 (TLR7), tripartite motif-containing protein 5 (TRIM5), and two killer-cell immunoglobulin-like receptors (KIR2DL1 and KIR2DL3). Additionally, SNPs that associated with progression from HIV infection to AIDS were identified in two 2'-5'-oligoadenylate synthetase genes (OAS2 and OAS3). In contrast, other SNPs identified in OAS2 and OAS3 genes, as well as in the TRIM5 and KIR2DS4 genes, were associated with a slower progression of disease. Taken together, our data demonstrates the utility of ultra-high multiplex PCR in identifying polymorphisms of potential clinical significance and further,identifies SNPs that may play a role in HIV pathogenesis.