Increasing consistency of disease biomarker prediction across datasets

Microarray studies with human subjects often have limited sample sizes which hampers the ability to detect reliable biomarkers associated with disease and motivates the need to aggregate data across studies. However, human gene expression measurements may be influenced by many non-random factors such as genetics, sample preparations, and tissue heterogeneity. These factors can contribute to a lack of agreement among related studies, limiting the utility of their aggregation. We show that it is feasible to carry out an automatic correction of individual datasets to reduce the effect of such 'latent variables' (without prior knowledge of the variables) in such a way that datasets addressing the same condition show better agreement once each is corrected. We build our approach on the method of surrogate variable analysis but we demonstrate that the original algorithm is unsuitable for the analysis of human tissue samples that are mixtures of different cell types. We propose a modification to SVA that is crucial to obtaining the improvement in agreement that we observe. We develop our method on a compendium of multiple sclerosis data and verify it on an independent compendium of Parkinson's disease datasets. In both cases, we show that our method is able to improve agreement across varying study designs, platforms, and tissues. This approach has the potential for wide applicability to any field where lack of inter-study agreement has been a concern. © 2014 Chikina, Sealfon

Transcription factor motifs associated with anterior insula gene-expression underlying mood disorder phenotypes

Background: Mood disorders represent a major cause of morbidity and mortality worldwide but the brain-related molecular pathophysiology in mood disorders remains largely undefined. Methods: Because the anterior insula is reduced in volume in patients with mood disorders, RNA was extracted from postmortem mood disorder samples and compared with unaffected control samples for RNA-sequencing identification of differentially expressed genes (DEGs) in a) bipolar disorder (BD; n=37) versus (vs.) controls (n=33), and b) major depressive disorder (MDD n=30) vs controls, and c) low vs. high Axis-I comorbidity (a measure of cumulative psychiatric disease burden). Given the regulatory role of transcription factors (TFs) in gene expression via specific-DNA-binding domains (motifs), we used JASPAR TF binding database to identify TF-motifs. Results: We found that DEGs in BD vs. controls, MDD vs. controls, and high vs. low Axis-I comorbidity were associated with TF-motifs that are known to regulate expression of toll-like receptor genes, cellular homeostatic-control genes, and genes involved in embryonic, cellular/organ and brain development. Discussion: Robust imaging-guided transcriptomics (i.e., using meta-analytic imaging results to guide independent post-mortem dissection for RNA-sequencing) was applied by targeting the gray matter volume reduction in the anterior insula in mood disorders, to guide independent postmortem identification of TF motifs regulating DEG. TF motifs were identified for immune, cellular, embryonic and neurodevelopmental processes. Conclusion: Our findings of TF-motifs that regulate the expression of immune, cellular homeostatic-control, and developmental genes provides novel information about the hierarchical .CC-BY-NC-ND 4.0 International licenseunder anot certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available The copyright holder for this preprint (which wasthis version posted September 28, 2020. ; https://doi.org/10.1101/864900doi: bioRxiv preprint 3 relationship between gene regulatory networks, the TFs that control them, and proximate underlying neuroanatomical phenotypes in mood disorders

Transcription Factor Motifs Associated with Anterior Insula Gene Expression Underlying Mood Disorder Phenotypes

Mood disorders represent a major cause of morbidity and mortality worldwide but the brain-related molecular pathophysiology in mood disorders remains largely undefined. Because the anterior insula is reduced in volume in patients with mood disorders, RNA was extracted from the anterior insula postmortem anterior insula of mood disorder samples and compared with unaffected controls for RNA-sequencing identification of differentially expressed genes (DEGs) in (a) bipolar disorder (BD; n = 37) versus (vs.) controls (n = 33), and (b) major depressive disorder (MDD n = 30) vs. controls, and (c) low vs. high axis I comorbidity (a measure of cumulative psychiatric disease burden). Given the regulatory role of transcription factors (TFs) in gene expression via specific-DNA-binding domains (motifs), we used JASPAR TF binding database to identify TF-motifs. We found that DEGs in BD vs. controls, MDD vs. controls, and high vs. low axis I comorbidity were associated with TF-motifs that are known to regulate expression of toll-like receptor genes, cellular homeostatic-control genes, and genes involved in embryonic, cellular/organ, and brain development. Robust imaging-guided transcriptomics by using meta-analytic imaging results to guide independent postmortem dissection for RNA-sequencing was applied by targeting the gray matter volume reduction in the anterior insula in mood disorders, to guide independent postmortem identification of TF motifs regulating DEG. Our findings of TF-motifs that regulate the expression of immune, cellular homeostatic-control, and developmental genes provide novel information about the hierarchical relationship between gene regulatory networks, the TFs that control them, and proximate underlying neuroanatomical phenotypes in mood disorders

Neuro-transcriptomic signatures for mood disorder morbidity and suicide mortality

Suicidal behaviors are strongly linked with mood disorders, but the specific neurobiological and functional gene-expression correlates for this linkage remain elusive. We performed neuroimaging-guided RNA-sequencing in two studies to test the hypothesis that imaging-localized gray matter volume (GMV) loss in mood disorders, harbors gene-expression changes associated with disease morbidity and related suicide mortality in an independent postmortem cohort. To do so, first, we conducted study 1 using an anatomical likelihood estimation (ALE) MRI meta-analysis including a total of 47 voxel-based morphometry (VBM) publications (i.e. 26 control versus (vs) major depressive disorder (MDD) studies, and 21 control vs bipolar disorder (BD) studies) in 2387 (living) participants. Study 1 meta-analysis identified a selective anterior insula cortex (AIC) GMV loss in mood disorders. We then used this results to guide study 2 postmortem tissue dissection and RNA-Sequencing of 100 independent donor brain samples with a life-time history of MDD (N = 30), BD (N = 37) and control (N = 33). In study 2, exploratory factor-analysis identified a higher-order factor representing number of Axis-1 diagnoses (e.g. substance use disorders/psychosis/anxiety, etc.), referred to here as morbidity and suicide-completion referred to as mortality. Comparisons of case-vs-control, and factor-analysis defined higher-order-factor contrast variables revealed that the imaging-identified AIC GMV loss sub-region harbors differential gene-expression changes in high morbidity-&-mortality versus low morbidity-&-mortality cohorts in immune, inflammasome, and neurodevelopmental pathways. Weighted gene co-expression network analysis further identified co-activated gene modules for psychiatric morbidity and mortality outcomes. These results provide evidence that AIC anatomical signature for mood disorders are possible correlates for gene-expression abnormalities in mood morbidity and suicide mortality

Gene Expression Profile and Functionality of ESC-Derived Lin-ckit+Sca-1+ Cells Are Distinct from Lin-ckit+Sca-1+ Cells Isolated from Fetal Liver or Bone Marrow

In vitro bioreactor-based cultures are being extensively investigated for large-scale production of differentiated cells from embryonic stem cells (ESCs). However, it is unclear whether in vitro ESC-derived progenitors have similar gene expression profiles and functionalities as their in vivo counterparts. This is crucial in establishing the validity of ESC-derived cells as replacements for adult-isolated cells for clinical therapies. In this study, we compared the gene expression profiles of Lin-ckit+Sca-1+ (LKS) cells generated in vitro from mouse ESCs using either static or bioreactor-based cultures, with that of native LKS cells isolated from mouse fetal liver (FL) or bone marrow (BM). We found that in vitro-generated LKS cells were more similar to FL- than to BM LKS cells in gene expression. Further, when compared to cells derived from bioreactor cultures, static culture-derived LKS cells showed fewer differentially expressed genes relative to both in vivo LKS populations. Overall, the expression of hematopoietic genes was lower in ESC-derived LKS cells compared to cells from BM and FL, while the levels of non-hematopoietic genes were up-regulated. In order to determine if these molecular profiles correlated with functionality, we evaluated ESC-derived LKS cells for in vitro hematopoietic-differentiation and colony formation (CFU assay). Although static culture-generated cells failed to form any colonies, they did differentiate into CD11c+ and B220+ cells indicating some hematopoietic potential. In contrast, bioreactor-derived LKS cells, when differentiated under the same conditions failed to produce any B220+ or CD11c+ cells and did not form colonies, indicating that these cells are not hematopoietic progenitors. We conclude that in vitro culture conditions significantly affect the transcriptome and functionality of ESC-derived LKS cells and although in vitro differentiated LKS cells were lineage negative and expressed both ckit and Sca-1, these cells, especially those obtained from dynamic cultures, are significantly different from native cells of the same phenotype.This work was partially supported through National Institutes of Health grant number EB005026 to KR and PWT. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. No additional external funding received for this study.Biomedical Engineerin

Effects of Salt Stress on Transcriptional and Physiological Responses in Barley Leaves with Contrasting Salt Tolerance

Salt stress negatively impacts crop production worldwide. Genetic diversity among barley (Hordeum vulgare) landraces adapted to adverse conditions should provide a valuable reservoir of tolerance genes for breeding programs. To identify molecular and biochemical differences between barley genotypes, transcriptomic and antioxidant enzyme profiles along with several morpho-physiological features were compared between salt-tolerant (Boulifa) and salt-sensitive (Testour) genotypes subjected to salt stress. Decreases in biomass, photosynthetic parameters, and relative water content were low in Boulifa compared to Testour. Boulifa had better antioxidant protection against salt stress than Testour, with greater antioxidant enzymes activities including catalase, superoxide dismutase, and guaiacol peroxidase. Transcriptome assembly for both genotypes revealed greater accumulation of differentially expressed transcripts in Testour compared to Boulifa, emphasizing the elevated transcriptional response in Testour following salt exposure. Various salt-responsive genes, including the antioxidant catalase 3, the osmoprotectant betaine aldehyde dehydrogenase 2, and the transcription factors MYB20 and MYB41, were induced only in Boulifa. By contrast, several genes associated with photosystems I and II, and light receptor chlorophylls A and B, were more repressed in Testour. Co-expression network analysis identified specific gene modules correlating with differences in genotypes and morpho-physiological traits. Overall, salinity-induced differential transcript accumulation underlies the differential morpho-physiological response in both genotypes and could be important for breeding salt tolerance in barley

Transcriptomic Analysis of Salt-Stress-Responsive Genes in Barley Roots and Leaves

Barley is characterized by a rich genetic diversity, making it an important model for studies of salinity response with great potential for crop improvement. Moreover, salt stress severely affects barley growth and development, leading to substantial yield loss. Leaf and root transcriptomes of a salt-tolerant Tunisian landrace (Boulifa) exposed to 2, 8, and 24 h salt stress were compared with pre-exposure plants to identify candidate genes and pathways underlying barley’s response. Expression of 3585 genes was upregulated and 5586 downregulated in leaves, while expression of 13,200 genes was upregulated and 10,575 downregulated in roots. Regulation of gene expression was severely impacted in roots, highlighting the complexity of salt stress response mechanisms in this tissue. Functional analyses in both tissues indicated that response to salt stress is mainly achieved through sensing and signaling pathways, strong transcriptional reprograming, hormone osmolyte and ion homeostasis stabilization, increased reactive oxygen scavenging, and activation of transport and photosynthesis systems. A number of candidate genes involved in hormone and kinase signaling pathways, as well as several transcription factor families and transporters, were identified. This study provides valuable information on early salt-stress-responsive genes in roots and leaves of barley and identifies several important players in salt tolerance

Drug resistance against HCV NS3/4A inhibitors is defined by the balance of substrate recognition versus inhibitor binding

Hepatitis C virus infects an estimated 180 million people worldwide, prompting enormous efforts to develop inhibitors targeting the essential NS3/4A protease. Resistance against the most promising protease inhibitors, telaprevir, boceprevir, and ITMN-191, has emerged in clinical trials. In this study, crystal structures of the NS3/4A protease domain reveal that viral substrates bind to the protease active site in a conserved manner defining a consensus volume, or substrate envelope. Mutations that confer the most severe resistance in the clinic occur where the inhibitors protrude from the substrate envelope, as these changes selectively weaken inhibitor binding without compromising the binding of substrates. These findings suggest a general model for predicting the susceptibility of protease inhibitors to resistance: drugs designed to fit within the substrate envelope will be less susceptible to resistance, as mutations affecting inhibitor binding would simultaneously interfere with the recognition of viral substrates