RNA alternative splicing impacts the risk for alcohol use disorder.

Alcohol use disorder (AUD) is a complex genetic disorder characterized by problems arising from excessive alcohol consumption. Identifying functional genetic variations that contribute to risk for AUD is a major goal. Alternative splicing of RNA mediates the flow of genetic information from DNA to gene expression and expands proteome diversity. We asked whether alternative splicing could be a risk factor for AUD. Herein, we used a Mendelian randomization (MR)-based approach to identify skipped exons (the predominant splicing event in brain) that contribute to AUD risk. Genotypes and RNA-seq data from the CommonMind Consortium were used as the training dataset to develop predictive models linking individual genotypes to exon skipping in the prefrontal cortex. We applied these models to data from the Collaborative Studies on Genetics of Alcoholism to examine the association between the imputed cis-regulated splicing outcome and the AUD-related traits. We identified 27 exon skipping events that were predicted to affect AUD risk; six of these were replicated in the Australian Twin-family Study of Alcohol Use Disorder. Their host genes are DRC1, ELOVL7, LINC00665, NSUN4, SRRM2 and TBC1D5. The genes downstream of these splicing events are enriched in neuroimmune pathways. The MR-inferred impacts of the ELOVL7 skipped exon on AUD risk was further supported in four additional large-scale genome-wide association studies. Additionally, this exon contributed to changes of gray matter volumes in multiple brain regions, including the visual cortex known to be involved in AUD. In conclusion, this study provides strong evidence that RNA alternative splicing impacts the susceptibility to AUD and adds new information on AUD-relevant genes and pathways. Our framework is also applicable to other types of splicing events and to other complex genetic disorders.

Bioinformatics detection of modulators controlling splicing factor-dependent intron retention in the human brain.

Alternative RNA splicing is an important means of genetic control and transcriptome diversity. However, when alternative splicing events are studied independently, coordinated splicing modulated by common factors is often not recognized. As a result, the molecular mechanisms of how splicing regulators promote or repress splice site recognition in a context-dependent manner are not well understood. The functional coupling between multiple gene regulatory layers suggests that splicing is modulated by additional genetic or epigenetic components. Here, we developed a bioinformatics approach to identify causal modulators of splicing activity based on the variation of gene expression in large RNA sequencing datasets. We applied this approach in a neurological context with hundreds of dorsolateral prefrontal cortex samples. Our model is strengthened with the incorporation of genetic variants to impute gene expression in a Mendelian randomization-based approach. We identified novel modulators of the splicing factor SRSF1, including UIMC1 and the long noncoding RNA CBR3-AS1, that function over dozens of SRSF1 intron retention splicing targets. This strategy can be widely used to identify modulators of RNA-binding proteins involved in tissue-specific alternative splicing.

Allele-specific expression and high-throughput reporter assay reveal functional genetic variants associated with alcohol use disorders.

Genome-wide association studies (GWAS) of complex traits, such as alcohol use disorders (AUD), usually identify variants in non-coding regions and cannot by themselves distinguish whether the associated variants are functional or in linkage disequilibrium with the functional variants. Transcriptome studies can identify genes whose expression differs between alcoholics and controls. To test which variants associated with AUD may cause expression differences, we integrated data from deep RNA-seq and GWAS of four postmortem brain regions from 30 subjects with AUD and 30 controls to analyze allele-specific expression (ASE). We identified 88 genes with differential ASE in subjects with AUD compared to controls. Next, to test one potential mechanism contributing to the differential ASE, we analyzed single nucleotide polymorphisms (SNPs) in the 3' untranslated regions (3'UTR) of these genes. Of the 88 genes with differential ASE, 61 genes contained 437 SNPs in the 3'UTR with at least one heterozygote among the subjects studied. Using a modified PASSPORT-seq (parallel assessment of polymorphisms in miRNA target-sites by sequencing) assay, we identified 25 SNPs that affected RNA levels in a consistent manner in two neuroblastoma cell lines, SH-SY5Y and SK-N-BE(2). Many of these SNPs are in binding sites of miRNAs and RNA-binding proteins, indicating that these SNPs are likely causal variants of AUD-associated differential ASE. In sum, we demonstrate that a combination of computational and experimental approaches provides a powerful strategy to uncover functionally relevant variants associated with the risk for AUD.

Glyphosate exposure in early pregnancy and reduced fetal growth: a prospective observational study of high-risk pregnancies.

BACKGROUND: Prenatal glyphosate (GLY) exposure is associated with adverse reproductive outcomes in animal studies. Little is known about the effects of GLY exposure during pregnancy in the human population. This study aims to establish baseline urine GLY levels in a high-risk and racially diverse pregnancy cohort and to assess the relationship between prenatal GLY exposure and fetal development and birth outcomes. METHODS: Random first trimester urine specimens were collected from high risk pregnant women between 2013 and 2016 as part of the Indiana Pregnancy Environmental Exposures Study (PEES). Demographic and clinical data were abstracted from mother and infant medical records. Urine glyphosate levels were measured as a proxy for GLY exposure and quantified using liquid chromatography-tandem mass spectrometry. Primary outcome variables included gestation-adjusted birth weight percentile (BWT%ile) and neonatal intensive care unit (NICU) admission. Relationships between primary outcome variables and GLY exposure were assessed using univariate and multivariate linear and logistic regression models. RESULTS: Urine GLY levels above the limit of detection (0.1 ng/mL) were found in 186 of 187 (99%) pregnant women. Further analyses were limited to 155 pregnant women with singleton live births. The mean age of participants was 29 years, and the majority were non-Hispanic white (70%) or non-Hispanic Black (21%). The mean (± SD) urine GLY level was 3.33 ± 1.67 ng/mL. Newborn BWT%iles were negatively related to GLY (adjusted slope ± SE = -0.032 + 0.014, p = 0.023). Infants born to women living outside of Indiana's large central metropolitan area were more likely to have a lower BWT%ile associated with mother's first trimester GLY levels (slope ± SE = -0.064 ± 0.024, p = 0.007). The adjusted odds ratio for NICU admission and maternal GLY levels was 1.16 (95% CI: 0.90, 1.67, p = 0.233). CONCLUSION: GLY was found in 99% of pregnant women in this Midwestern cohort. Higher maternal GLY levels in the first trimester were associated with lower BWT%iles and higher NICU admission risk. The results warrant further investigation on the effects of GLY exposure in human pregnancies in larger population studies.

Functional 3'-UTR Variants Identify Regulatory Mechanisms Impacting Alcohol Use Disorder and Related Traits.

Although genome-wide association studies (GWAS) have identified loci associated with alcohol consumption and alcohol use disorder (AUD), they do not identify which variants are functional. To approach this, we evaluated the impact of variants in 3' untranslated regions (3'-UTRs) of genes in loci associated with substance use and neurological disorders using a massively parallel reporter assay (MPRA) in neuroblastoma and microglia cells. Functionally impactful variants explained a higher proportion of heritability of alcohol traits than non-functional variants. We identified genes whose 3'UTR activities are associated with AUD and alcohol consumption by combining variant effects from MPRA with GWAS results. We examined their effects by evaluating gene expression after CRISPR inhibition of neuronal cells and stratifying brain tissue samples by MPRA-derived 3'-UTR activity. A pathway analysis of differentially expressed genes identified inflammation response pathways. These analyses suggest that variation in response to inflammation contributes to the propensity to increase alcohol consumption.

Genetic Regulation of Human isomiR Biogenesis.

MicroRNAs play a critical role in regulating gene expression post-transcriptionally. Variations in mature microRNA sequences, known as isomiRs, arise from imprecise cleavage and nucleotide substitution or addition. These isomiRs can target different mRNAs or compete with their canonical counterparts, thereby expanding the scope of miRNA post-transcriptional regulation. Our study investigated the relationship between cis-acting single-nucleotide polymorphisms (SNPs) in precursor miRNA regions and isomiR composition, represented by the ratio of a specific 5'-isomiR subtype to all isomiRs identified for a particular mature miRNA. Significant associations between 95 SNP-isomiR pairs were identified. Of note, rs6505162 was significantly associated with both the 5'-extension of hsa-miR-423-3p and the 5'-trimming of hsa-miR-423-5p. Comparison of breast cancer and normal samples revealed that the expression of both isomiRs was significantly higher in tumors than in normal tissues. This study sheds light on the genetic regulation of isomiR maturation and advances our understanding of post-transcriptional regulation by microRNAs.

Gene Expression Alterations in Peripheral Blood Following Sport-Related Concussion in a Prospective Cohort of Collegiate Athletes: A Concussion Assessment, Research and Education (CARE) Consortium Study.

BACKGROUND: Molecular-based approaches to understanding concussion pathophysiology provide complex biological information that can advance concussion research and identify potential diagnostic and/or prognostic biomarkers of injury. OBJECTIVE: The aim of this study was to identify gene expression changes in peripheral blood that are initiated following concussion and are relevant to concussion response and recovery. METHODS: We analyzed whole blood transcriptomes in a large cohort of concussed and control collegiate athletes who were participating in the multicenter prospective cohort Concussion Assessment, Research, and Education (CARE) Consortium study. Blood samples were collected from collegiate athletes at preseason (baseline), within 6 h of concussion injury, and at four additional prescribed time points spanning 24 h to 6 months post-injury. RNA sequencing was performed on samples from 230 concussed, 130 contact control, and 102 non-contact control athletes. Differential gene expression and deconvolution analysis were performed at each time point relative to baseline. RESULTS: Cytokine and immune response signaling pathways were activated immediately after concussion, but at later time points these pathways appeared to be suppressed relative to the contact control group. We also found that the proportion of neutrophils increased and natural killer cells decreased in the blood following concussion. CONCLUSIONS: Transcriptome signatures in the blood reflect the known pathophysiology of concussion and may be useful for defining the immediate biological response and the time course for recovery. In addition, the identified immune response pathways and changes in immune cell type proportions following a concussion may inform future treatment strategies.

Intron-Retention Neoantigen Load Predicts Favorable Prognosis in Pancreatic Cancer.

PURPOSE: High tumor mutation burden (TMB) in many cancer types is associated with the production of tumor-specific neoantigens, a favorable outcome and response to immune checkpoint blockade (ICB) therapy. Besides mutation-derived neoantigens, aberrant intron retention also produces tumor neopeptides that could trigger an immune response. The relationship between intron-retention-derived tumor neoantigens (IR-neoAg) and clinical outcomes in pancreatic cancer remains uncertain. Here, we quantify IR-neoAg in pancreatic cancer and evaluate whether IR-neoAg load might serve as a biomarker for selecting patients who may benefit from ICB therapy. METHODS: We developed a computational approach to estimate patient-specific IR-neoAg load from transcriptome data available in The Cancer Genome Atlas pancreatic cancer cohort. Associations between IR-neoAg load and patient overall survival were evaluated using Kaplan-Meier estimates and Cox regression. Differential expression of immune checkpoint and HLA-I genes was evaluated in tumors with high IR-neoAg load. RESULTS: High IR-neoAg load predicted better overall survival in pancreatic cancer, although no association was found for TMB. IR-neoAg load remained a significant prognostic factor after adjusting for patient age, sex, tumor stage and grade, and TMB. Moreover, pancreatic tumors with both high IR-neoAg load and high HLA-I gene expression had similar gene expression profiles as other tumor types that showed response to anti-programmed cell death protein 1 therapy. CONCLUSION: IR-neoAg load is associated with favorable survival in pancreatic cancer. These findings provide strong evidence for considering IR-neoAgs when selecting patients who might benefit from ICB therapy.

Differential Splicing of Skipped Exons Predicts Drug Response in Cancer Cell Lines.

Alternative splicing of pre-mRNA transcripts is an important regulatory mechanism that increases the diversity of gene products in eukaryotes. Various studies have linked specific transcript isoforms to altered drug response in cancer; however, few algorithms have incorporated splicing information into drug response prediction. In this study, we evaluated whether basal-level splicing information could be used to predict drug sensitivity by constructing doxorubicin-sensitivity classification models with splicing and expression data. We detailed splicing differences between sensitive and resistant cell lines by implementing quasi-binomial generalized linear modeling (QBGLM) and found altered inclusion of 277 skipped exons. We additionally conducted RNA-binding protein (RBP) binding motif enrichment and differential expression analysis to characterize cis- and trans-acting elements that potentially influence doxorubicin response-mediating splicing alterations. Our results showed that a classification model built with skipped exon data exhibited strong predictive power. We discovered an association between differentially spliced events and epithelial-mesenchymal transition (EMT) and observed motif enrichment, as well as differential expression of RBFOX and ELAVL RBP family members. Our work demonstrates the potential of incorporating splicing data into drug response algorithms and the utility of a QBGLM approach for fast, scalable identification of relevant splicing differences between large groups of samples.

Intron retention-induced neoantigen load correlates with unfavorable prognosis in multiple myeloma.

Neoantigen peptides arising from genetic alterations may serve as targets for personalized cancer vaccines and as positive predictors of response to immune checkpoint therapy. Mutations in genes regulating RNA splicing are common in hematological malignancies leading to dysregulated splicing and intron retention (IR). In this study, we investigated IR as a potential source of tumor neoantigens in multiple myeloma (MM) patients and the relationship of IR-induced neoantigens (IR-neoAg) with clinical outcomes. MM-specific IR events were identified in RNA-sequencing data from the Multiple Myeloma Research Foundation CoMMpass study after removing IR events that also occurred in normal plasma cells. We quantified the IR-neoAg load by assessing IR-induced novel peptides that were predicted to bind to major histocompatibility complex (MHC) molecules. We found that high IR-neoAg load was associated with poor overall survival in both newly diagnosed and relapsed MM patients. Further analyses revealed that poor outcome in MM patients with high IR-neoAg load was associated with high expression levels of T-cell co-inhibitory molecules and elevated interferon signaling activity. We also found that MM cells exhibiting high IR levels had lower MHC-II protein abundance and treatment of MM cells with a spliceosome inhibitor resulted in increased MHC-I protein abundance. Our findings suggest that IR-neoAg may represent a novel biomarker of MM patient clinical outcome and further that targeting RNA splicing may serve as a potential therapeutic strategy to prevent MM immune escape and promote response to checkpoint blockade.

Cryopreservation Preserves Cell-Type Composition and Gene Expression Profiles in Bone Marrow Aspirates From Multiple Myeloma Patients.

Single-cell RNA sequencing reveals gene expression differences between individual cells and also identifies different cell populations that are present in the bulk starting material. To obtain an accurate assessment of patient samples, single-cell suspensions need to be generated as soon as possible once the tissue or sample has been collected. However, this requirement poses logistical challenges for experimental designs involving multiple samples from the same subject since these samples would ideally be processed at the same time to minimize technical variation in data analysis. Although cryopreservation has been shown to largely preserve the transcriptome, it is unclear whether the freeze-thaw process might alter gene expression profiles in a cell-type specific manner or whether changes in cell-type proportions might also occur. To address these questions in the context of multiple myeloma clinical studies, we performed single-cell RNA sequencing (scRNA-seq) to compare fresh and frozen cells isolated from bone marrow aspirates of six multiple myeloma patients, analyzing both myeloma cells (CD138+) and cells constituting the microenvironment (CD138-). We found that cryopreservation using 90% fetal calf serum and 10% dimethyl sulfoxide resulted in highly consistent gene expression profiles when comparing fresh and frozen samples from the same patient for both CD138+ myeloma cells (R ≥ 0.96) and for CD138- cells (R ≥ 0.9). We also demonstrate that CD138- cell-type proportions showed minimal alterations, which were mainly related to small differences in immune cell subtype sensitivity to the freeze-thaw procedures. Therefore, when processing fresh multiple myeloma samples is not feasible, cryopreservation is a useful option in single-cell profiling studies.

New platform for controlled and sustained delivery of the EGF receptor tyrosine kinase inhibitor AG1478 using poly(lactic-co-glycolic acid) microspheres.

Inhibition of the epidermal growth factor receptor (EGFR) reduces tumour growth and metastases and promotes axon regeneration in the central nervous system. Current EGFR inhibition strategies include the administration of reversible small-molecule tyrosine kinase inhibitors (TKIs). However, to be effective in vivo sustained delivery is required. This study explored the feasibility of encapsulating the tyrphostin 4-(3-chloroanilino)-6,7-dimethoxyquinazoline (AG1478) in poly(lactic-co-glycolic acid) (PLGA) microspheres using three different emulsion methods: solid-in-oil-in-water, oil-in-water and oil-in-water with co-solvent. Addition of a co-solvent increased loading and release of AG1478 and significantly (p < 0.001) decreased microsphere size. Co-solvent addition also prolonged AG1478 release from 6 months to over 9 months. Once released AG1478 remained bioactive and inhibited EGFR in immortalized rat fibroblasts and EGFR-amplified human carcinoma cells. These results demonstrate that AG1478 can be encapsulated in PLGA with sustained release and retain bioactivity; thereby providing a new platform for controlled administration of EGFR TKIs.

Integrative analysis of histopathological images and chromatin accessibility data for estrogen receptor-positive breast cancer.

BACKGROUND: Existing studies have demonstrated that the integrative analysis of histopathological images and genomic data can be used to better understand the onset and progression of many diseases, as well as identify new diagnostic and prognostic biomarkers. However, since the development of pathological phenotypes are influenced by a variety of complex biological processes, complete understanding of the underlying gene regulatory mechanisms for the cell and tissue morphology is still a challenge. In this study, we explored the relationship between the chromatin accessibility changes and the epithelial tissue proportion in histopathological images of estrogen receptor (ER) positive breast cancer. METHODS: An established whole slide image processing pipeline based on deep learning was used to perform global segmentation of epithelial and stromal tissues. We then used canonical correlation analysis to detect the epithelial tissue proportion-associated regulatory regions. By integrating ATAC-seq data with matched RNA-seq data, we found the potential target genes that associated with these regulatory regions. Then we used these genes to perform the following pathway and survival analysis. RESULTS: Using canonical correlation analysis, we detected 436 potential regulatory regions that exhibited significant correlation between quantitative chromatin accessibility changes and the epithelial tissue proportion in tumors from 54 patients (FDR < 0.05). We then found that these 436 regulatory regions were associated with 74 potential target genes. After functional enrichment analysis, we observed that these potential target genes were enriched in cancer-associated pathways. We further demonstrated that using the gene expression signals and the epithelial tissue proportion extracted from this integration framework could stratify patient prognoses more accurately, outperforming predictions based on only omics or image features. CONCLUSION: This integrative analysis is a useful strategy for identifying potential regulatory regions in the human genome that are associated with tumor tissue quantification. This study will enable efficient prioritization of genomic regulatory regions identified by ATAC-seq data for further studies to validate their causal regulatory function. Ultimately, identifying epithelial tissue proportion-associated regulatory regions will further our understanding of the underlying molecular mechanisms of disease and inform the development of potential therapeutic targets.

Epigenetic changes on rat chromosome 4 contribute to disparate alcohol drinking behavior in alcohol-preferring and -nonpreferring rats.

BACKGROUND: Paternal alcohol abuse is a well-recognized risk factor for the development of an alcohol use disorder (AUD). In addition to genetic and environmental risk factors, heritable epigenetic factors also have been proposed to play a key role in the development of AUD. However, it is not clear whether epigenetic factors contribute to the genetic inheritance in families affected by AUD. We used reciprocal crosses of the alcohol-preferring (P) and -nonpreferring (NP) rat lines to test whether epigenetic factors also impacted alcohol drinking in up to two generations of offspring. METHODS: F1 offspring derived by reciprocal breeding of P and NP rats were tested for differences in alcohol consumption using a free-choice protocol of 10% ethanol, 20% ethanol, and water that were available concurrently. In a separate experiment, an F2 population was tested for alcohol consumption not only due to genetic differences. These rats were generated from inbred P (iP) and iNP rat lines that were reciprocally bred to produce genetically identical F1 offspring that remained alcohol-naïve. Intercrosses of the F1 generation animals produced the F2 generation. Alcohol consumption was then assessed in the F2 generation using a standard two-bottle choice protocol, and was analyzed using genome-wide linkage analysis. Alcohol consumption measures were also analyzed for sex differences. RESULTS: Average alcohol consumption was higher in the F1 offspring of P vs. NP sires and in the F2 offspring of F0 iP vs. iNP grandsires. Linkage analyses showed the maximum LOD scores for alcohol consumption in both male and female offspring were on chromosome 4 (Chr 4). The LOD score for both sexes considered together was higher when the grandsire was iP vs. iNP (5.0 vs. 3.35, respectively). Furthermore, the F2 population displayed enhanced alcohol consumption when the P alleles from the F0 sire were present. CONCLUSIONS: These results demonstrate that epigenetic and/or non-genetic factors mapping to rat chromosome 4 contribute to a transgenerational paternal effect on alcohol consumption in the P and NP rat model of AUD.

Highly robust model of transcription regulator activity predicts breast cancer overall survival.

BACKGROUND: While several multigene signatures are available for predicting breast cancer prognosis, particularly in early stage disease, effective molecular indicators are needed, especially for triple-negative carcinomas, to improve treatments and predict diagnostic outcomes. The objective of this study was to identify transcriptional regulatory networks to better understand mechanisms giving rise to breast cancer development and to incorporate this information into a model for predicting clinical outcomes. METHODS: Gene expression profiles from 1097 breast cancer patients were retrieved from The Cancer Genome Atlas (TCGA). Breast cancer-specific transcription regulatory information was identified by considering the binding site information from ENCODE and the top co-expressed targets in TCGA using a nonlinear approach. We then used this information to predict breast cancer patient survival outcome. RESULT: We built a multiple regulator-based prediction model for breast cancer. This model was validated in more than 5000 breast cancer patients from the Gene Expression Omnibus (GEO) databases. We demonstrated our regulator model was significantly associated with clinical stage and that cell cycle and DNA replication related pathways were significantly enriched in high regulator risk patients. CONCLUSION: Our findings demonstrate that transcriptional regulator activities can predict patient survival. This finding provides additional biological insights into the mechanisms of breast cancer progression.

regSNPs-ASB: A Computational Framework for Identifying Allele-Specific Transcription Factor Binding From ATAC-seq Data.

Expression quantitative trait loci (eQTL) analysis is useful for identifying genetic variants correlated with gene expression, however, it cannot distinguish between causal and nearby non-functional variants. Because the majority of disease-associated SNPs are located in regulatory regions, they can impact allele-specific binding (ASB) of transcription factors and result in differential expression of the target gene alleles. In this study, our aim was to identify functional single-nucleotide polymorphisms (SNPs) that alter transcriptional regulation and thus, potentially impact cellular function. Here, we present regSNPs-ASB, a generalized linear model-based approach to identify regulatory SNPs that are located in transcription factor binding sites. The input for this model includes ATAC-seq (assay for transposase-accessible chromatin with high-throughput sequencing) raw read counts from heterozygous loci, where differential transposase-cleavage patterns between two alleles indicate preferential transcription factor binding to one of the alleles. Using regSNPs-ASB, we identified 53 regulatory SNPs in human MCF-7 breast cancer cells and 125 regulatory SNPs in human mesenchymal stem cells (MSC). By integrating the regSNPs-ASB output with RNA-seq experimental data and publicly available chromatin interaction data from MCF-7 cells, we found that these 53 regulatory SNPs were associated with 74 potential target genes and that 32 (43%) of these genes showed significant allele-specific expression. By comparing all of the MCF-7 and MSC regulatory SNPs to the eQTLs in the Genome-Tissue Expression (GTEx) Project database, we found that 30% (16/53) of the regulatory SNPs in MCF-7 and 43% (52/122) of the regulatory SNPs in MSC were also in eQTL regions. The enrichment of regulatory SNPs in eQTLs indicated that many of them are likely responsible for allelic differences in gene expression (chi-square test, p-value < 0.01). In summary, we conclude that regSNPs-ASB is a useful tool for identifying causal variants from ATAC-seq data. This new computational tool will enable efficient prioritization of genetic variants identified as eQTL for further studies to validate their causal regulatory function. Ultimately, identifying causal genetic variants will further our understanding of the underlying molecular mechanisms of disease and the eventual development of potential therapeutic targets.

The Access Technology Program of the Indiana Clinical Translational Sciences Institute (CTSI): A model to facilitate access to cutting-edge technologies across a state.

INTRODUCTION: Access to cutting-edge technologies is essential for investigators to advance translational research. The Indiana Clinical and Translational Sciences Institute (CTSI) spans three major and preeminent universities, four large academic campuses across the state of Indiana, and is mandate to provide best practices to a whole state. METHODS: To address the need to facilitate the availability of innovative technologies to its investigators, the Indiana CTSI implemented the Access Technology Program (ATP). The activities of the ATP, or any program of the Indiana CTSI, are challenged to connect technologies and investigators on the multiple Indiana CTSI campuses by the geographical distances between campuses (1-4 hr driving time). RESULTS: Herein, we describe the initiatives developed by the ATP to increase the availability of state-of-the-art technologies to its investigators on all Indiana CTSI campuses, and the methods developed by the ATP to bridge the distance between campuses, technologies, and investigators for the advancement of clinical translational research. CONCLUSIONS: The methods and practices described in this publication may inform other approaches to enhance translational research, dissemination, and usage of innovative technologies by translational investigators, especially when distance or multi-campus cultural differences are factors to efficient application.

Comprehensive Cis-Regulation Analysis of Genetic Variants in Human Lymphoblastoid Cell Lines.

Genetic variants can influence the expression of mRNA and protein. Genetic regulatory loci such as expression quantitative trait loci (eQTLs) and protein quantitative trait loci (pQTLs) exist in several species. However, it remains unclear how human genetic variants regulate mRNA and protein expression. Here, we characterized six mechanistic models for the genetic regulatory patterns of single-nucleotide polymorphisms (SNPs) and their actions on post-transcriptional expression. Data from Yoruba HapMap lymphoblastoid cell lines were analyzed to identify human cis-eQTLs and pQTLs, as well as protein-specific QTLs (psQTLs). Our results indicated that genetic regulatory loci primarily affected mRNA and protein abundance in patterns where the two were well-correlated. While this finding was observed in both humans and mice (57.5% and 70.3%, respectively), the genetic regulatory patterns differed between species, implying evolutionary differences. Mouse SNPs generally targeted changes in transcript expression (51%), whereas in humans, they largely regulated protein abundance, independent of transcription levels (55.9%). The latter independent function can be explained by psQTLs. Our analysis suggests that local functional genetic variants in the human genome mainly modulate protein abundance independent of mRNA levels through post-transcriptional mechanisms. These findings clarify the impact of genetic variation on phenotype, which is of particular relevance to disease risk and treatment response.

Lipopolysaccharides Improve Mesenchymal Stem Cell-Mediated Cardioprotection by MyD88 and stat3 Signaling in a Mouse Model of Cardiac Ischemia/Reperfusion Injury.

Bone marrow-derived mesenchymal stem cells (MSCs) improve cardiac function after ischemia/reperfusion injury, in part, due to the release of cytoprotective paracrine factors. Toll-like receptor 4 (TLR4) is expressed in MSCs and regulates the expression of cytoprotective factors, cytokines, and chemokines. Lipopolysaccharide (LPS) stimulation of TLR4 activates two distinct signaling pathways that are either MyD88 dependent or MyD88 independent/TIR-domain-containing adapter-inducing interferon-ß (TRIF) dependent. While it was reported previously that LPS treatment improved MSC-mediated cardioprotection, the mechanism underlying such improved effect remains unknown. To study the role of MyD88 signaling in MSC cardioprotective activity, wild type (WT) and MyD88-/- MSCs were treated with LPS (200 ng/mL) for 24 h. WT and MyD88-/- MSCs with or without LPS pretreatment were infused into the coronary circulation of isolated mouse hearts (Langendorff model) and then subjected to ischemia (25 min) and reperfusion (50 min). Saline served as a negative control. Both untreated and LPS-pretreated WT MSCs significantly improved postischemic recovery of myocardial function of isolated mouse hearts, as evidenced by improved left ventricular developed pressure and ventricular contractility assessment (ie, the rate of left ventricle pressure change over time, ± dp/dt). LPS-pretreated WT MSCs conferred better cardiac function recovery than untreated MSCs; however, such effect of LPS was abolished when using MyD88-/- MSCs. In addition, LPS stimulated stat3 activity in WT MSCs, but not MyD88-/- MSCs. stat3 small interfering RNA abolished the effect of LPS in improving the cardioprotection of WT MSCs. In conclusion, this study demonstrates that LPS improves MSC-mediated cardioprotection by MyD88-dependent activation of stat3.

RegSNPs-intron: a computational framework for predicting pathogenic impact of intronic single nucleotide variants.

Single nucleotide variants (SNVs) in intronic regions have yet to be systematically investigated for their disease-causing potential. Using known pathogenic and neutral intronic SNVs (iSNVs) as training data, we develop the RegSNPs-intron algorithm based on a random forest classifier that integrates RNA splicing, protein structure, and evolutionary conservation features. RegSNPs-intron showed excellent performance in evaluating the pathogenic impacts of iSNVs. Using a high-throughput functional reporter assay called ASSET-seq (ASsay for Splicing using ExonTrap and sequencing), we evaluate the impact of RegSNPs-intron predictions on splicing outcome. Together, RegSNPs-intron and ASSET-seq enable effective prioritization of iSNVs for disease pathogenesis.