Browsing by Subject "Gene Expression Profiling"
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Item Bile acid synthesis, modulation, and dementia: A metabolomic, transcriptomic, and pharmacoepidemiologic study(PLOS, 2021-05-27) Varma, Vijay R.; Wang, Youjin; An, Yang; Varma, Sudhir; Bilgel, Murat; Doshi, Jimit; Legido-Quigley, Cristina; Delgado, João C.; Oommen, Anup M.; Roberts, Jackson A.; Wong, Dean F.; Davatzikos, Christos; Resnick, Susan M.; Troncoso, Juan C.; Pletnikova, Olga; O’Brien, Richard; Hak, Eelko; Baak, Brenda N.; Pfeiffer, Ruth; Baloni, Priyanka; Mohmoudiandehkordi, Siamak; Nho, Kwangsik; Kaddurah-Daouk, Rima; Bennett, David A.; Gadalla, Shahinaz M.; Thambisetty, Madhav; Radiology and Imaging Sciences, School of MedicineBackground: While Alzheimer disease (AD) and vascular dementia (VaD) may be accelerated by hypercholesterolemia, the mechanisms underlying this association are unclear. We tested whether dysregulation of cholesterol catabolism, through its conversion to primary bile acids (BAs), was associated with dementia pathogenesis. Methods and findings: We used a 3-step study design to examine the role of the primary BAs, cholic acid (CA), and chenodeoxycholic acid (CDCA) as well as their principal biosynthetic precursor, 7α-hydroxycholesterol (7α-OHC), in dementia. In Step 1, we tested whether serum markers of cholesterol catabolism were associated with brain amyloid accumulation, white matter lesions (WMLs), and brain atrophy. In Step 2, we tested whether exposure to bile acid sequestrants (BAS) was associated with risk of dementia. In Step 3, we examined plausible mechanisms underlying these findings by testing whether brain levels of primary BAs and gene expression of their principal receptors are altered in AD. Step 1: We assayed serum concentrations CA, CDCA, and 7α-OHC and used linear regression and mixed effects models to test their associations with brain amyloid accumulation (N = 141), WMLs, and brain atrophy (N = 134) in the Baltimore Longitudinal Study of Aging (BLSA). The BLSA is an ongoing, community-based cohort study that began in 1958. Participants in the BLSA neuroimaging sample were approximately 46% male with a mean age of 76 years; longitudinal analyses included an average of 2.5 follow-up magnetic resonance imaging (MRI) visits. We used the Alzheimer's Disease Neuroimaging Initiative (ADNI) (N = 1,666) to validate longitudinal neuroimaging results in BLSA. ADNI is an ongoing, community-based cohort study that began in 2003. Participants were approximately 55% male with a mean age of 74 years; longitudinal analyses included an average of 5.2 follow-up MRI visits. Lower serum concentrations of 7α-OHC, CA, and CDCA were associated with higher brain amyloid deposition (p = 0.041), faster WML accumulation (p = 0.050), and faster brain atrophy mainly (false discovery rate [FDR] p = <0.001-0.013) in males in BLSA. In ADNI, we found a modest sex-specific effect indicating that lower serum concentrations of CA and CDCA were associated with faster brain atrophy (FDR p = 0.049) in males.Step 2: In the Clinical Practice Research Datalink (CPRD) dataset, covering >4 million registrants from general practice clinics in the United Kingdom, we tested whether patients using BAS (BAS users; 3,208 with ≥2 prescriptions), which reduce circulating BAs and increase cholesterol catabolism, had altered dementia risk compared to those on non-statin lipid-modifying therapies (LMT users; 23,483 with ≥2 prescriptions). Patients in the study (BAS/LMT) were approximately 34%/38% male and with a mean age of 65/68 years; follow-up time was 4.7/5.7 years. We found that BAS use was not significantly associated with risk of all-cause dementia (hazard ratio (HR) = 1.03, 95% confidence interval (CI) = 0.72-1.46, p = 0.88) or its subtypes. We found a significant difference between the risk of VaD in males compared to females (p = 0.040) and a significant dose-response relationship between BAS use and risk of VaD (p-trend = 0.045) in males.Step 3: We assayed brain tissue concentrations of CA and CDCA comparing AD and control (CON) samples in the BLSA autopsy cohort (N = 29). Participants in the BLSA autopsy cohort (AD/CON) were approximately 50%/77% male with a mean age of 87/82 years. We analyzed single-cell RNA sequencing (scRNA-Seq) data to compare brain BA receptor gene expression between AD and CON samples from the Religious Orders Study and Memory and Aging Project (ROSMAP) cohort (N = 46). ROSMAP is an ongoing, community-based cohort study that began in 1994. Participants (AD/CON) were approximately 56%/36% male with a mean age of 85/85 years. In BLSA, we found that CA and CDCA were detectable in postmortem brain tissue samples and were marginally higher in AD samples compared to CON. In ROSMAP, we found sex-specific differences in altered neuronal gene expression of BA receptors in AD. Study limitations include the small sample sizes in the BLSA cohort and likely inaccuracies in the clinical diagnosis of dementia subtypes in primary care settings. Conclusions: We combined targeted metabolomics in serum and amyloid positron emission tomography (PET) and MRI of the brain with pharmacoepidemiologic analysis to implicate dysregulation of cholesterol catabolism in dementia pathogenesis. We observed that lower serum BA concentration mainly in males is associated with neuroimaging markers of dementia, and pharmacological lowering of BA levels may be associated with higher risk of VaD in males. We hypothesize that dysregulation of BA signaling pathways in the brain may represent a plausible biologic mechanism underlying these results. Together, our observations suggest a novel mechanism relating abnormalities in cholesterol catabolism to risk of dementia.Item CTD: An information-theoretic algorithm to interpret sets of metabolomic and transcriptomic perturbations in the context of graphical models(PLOS, 2021-01) Thistlethwaite, Lillian R.; Petrosyan, Varduhi; Li, Xiqi; Miller, Marcus J.; Elsea, Sarah H.; Milosavljevic, Aleksandar; Medical and Molecular Genetics, School of MedicineWe consider the following general family of algorithmic problems that arises in transcriptomics, metabolomics and other fields: given a weighted graph G and a subset of its nodes S, find subsets of S that show significant connectedness within G. A specific solution to this problem may be defined by devising a scoring function, the Maximum Clique problem being a classic example, where S includes all nodes in G and where the score is defined by the size of the largest subset of S fully connected within G. Major practical obstacles for the plethora of algorithms addressing this type of problem include computational efficiency and, particularly for more complex scores which take edge weights into account, the computational cost of permutation testing, a statistical procedure required to obtain a bound on the p-value for a connectedness score. To address these problems, we developed CTD, "Connect the Dots", a fast algorithm based on data compression that detects highly connected subsets within S. CTD provides information-theoretic upper bounds on p-values when S contains a small fraction of nodes in G without requiring computationally costly permutation testing. We apply the CTD algorithm to interpret multi-metabolite perturbations due to inborn errors of metabolism and multi-transcript perturbations associated with breast cancer in the context of disease-specific Gaussian Markov Random Field networks learned directly from respective molecular profiling data.Item Gene profiling of maternal hepatic adaptations to pregnancy(Wiley Blackwell (Blackwell Publishing), 2010-03) Bustamante, Juan J.; Copple, Bryan L.; Soares, Michael J.; Dai, Guoli; Department of Biology, School of ScienceBACKGROUND: Maternal metabolic demands change dramatically during the course of gestation and must be co-ordinated with the needs of the developing placenta and fetus. The liver is critically involved in metabolism and other important functions. However, maternal hepatic adjustments to pregnancy are poorly understood. AIM: The aim of the study was to evaluate the influences of pregnancy on the maternal liver growth and gene expression profile. METHODS: Holtzman Sprague-Dawley rats were mated and sacrificed at various stages of gestation and post-partum. The maternal livers were analysed in gravimetric response, DNA content by PicoGreen dsDNA quantitation reagent, hepatocyte ploidy by flow cytometry and hepatocyte proliferation by ki-67 immunostaining. Gene expression profiling of non-pregnant and gestation d18.5 maternal hepatic tissue was analysed using a DNA microarray approach and partially verified by northern blot or quantitative real-time PCR analysis. RESULTS: During pregnancy, the liver exhibited approximately an 80% increase in size, proportional to the increase in body weight of the pregnant animals. The pregnancy-induced hepatomegaly was a physiological event of liver growth manifested by increases in maternal hepatic DNA content and hepatocyte proliferation. Pregnancy did not affect hepatocyte polyploidization. Pregnancy-dependent changes in hepatic expression were noted for a number of genes, including those associated with cell proliferation, cytokine signalling, liver regeneration and metabolism. CONCLUSIONS: The metabolic demands of pregnancy cause marked adjustments in maternal liver physiology. Central to these adjustments are an expansion in hepatic capacity and changes in hepatic gene expression. Our findings provide insights into pregnancy-dependent hepatic adaptations.Item Haemophilus ducreyi RpoE and CpxRA Appear To Play Distinct yet Complementary Roles in Regulation of Envelope-Related Functions(Journal of Bacteriology, 2014-12) Gangaiah, Dharanesh; Zhang, Xinjun; Baker, Beth; Fortney, Kate R.; Liu, Yunlong; Munson, Robert S. Jr.; Spinola, Stanley M.; Department of Microbiology & Immunology, IU School of MedicineHaemophilus ducreyi causes the sexually transmitted disease chancroid and a chronic limb ulceration syndrome in children. In humans, H. ducreyi is found in an abscess and overcomes a hostile environment to establish infection. To sense and respond to membrane stress, bacteria utilize two-component systems (TCSs) and extracytoplasmic function (ECF) sigma factors. We previously showed that activation of CpxRA, the only intact TCS in H. ducreyi, does not regulate homologues of envelope protein folding factors but does downregulate genes encoding envelope-localized proteins, including many virulence determinants. H. ducreyi also harbors a homologue of RpoE, which is the only ECF sigma factor in the organism. To potentially understand how H. ducreyi responds to membrane stress, here we defined RpoE-dependent genes using transcriptome sequencing (RNA-Seq). We identified 180 RpoE-dependent genes, of which 98% were upregulated; a major set of these genes encodes homologues of envelope maintenance and repair factors. We also identified and validated a putative RpoE promoter consensus sequence, which was enriched in the majority of RpoE-dependent targets. Comparison of RpoE-dependent genes to those controlled by CpxR showed that each transcription factor regulated a distinct set of genes. Given that RpoE activated a large number of genes encoding envelope maintenance and repair factors and that CpxRA represses genes encoding envelope-localized proteins, these data suggest that RpoE and CpxRA appear to play distinct yet complementary roles in regulating envelope homeostasis in H. ducreyi.Item HNRNPA1 promotes recognition of splice site decoys by U2AF2 in vivo(Cold Spring Harbor Laboratory Press, 2018-05) Howard, Jonathan M.; Lin, Hai; Wallace, Andrew J.; Kim, Garam; Draper, Jolene M.; Haeussler, Maximilian; Katzman, Sol; Toloue, Masoud; Liu, Yunlong; Sanford, Jeremy R.; Medical and Molecular Genetics, School of MedicineAlternative pre-mRNA splicing plays a major role in expanding the transcript output of human genes. This process is regulated, in part, by the interplay of trans-acting RNA binding proteins (RBPs) with myriad cis-regulatory elements scattered throughout pre-mRNAs. These molecular recognition events are critical for defining the protein-coding sequences (exons) within pre-mRNAs and directing spliceosome assembly on noncoding regions (introns). One of the earliest events in this process is recognition of the 3' splice site (3'ss) by U2 small nuclear RNA auxiliary factor 2 (U2AF2). Splicing regulators, such as the heterogeneous nuclear ribonucleoprotein A1 (HNRNPA1), influence spliceosome assembly both in vitro and in vivo, but their mechanisms of action remain poorly described on a global scale. HNRNPA1 also promotes proofreading of 3'ss sequences though a direct interaction with the U2AF heterodimer. To determine how HNRNPA1 regulates U2AF-RNA interactions in vivo, we analyzed U2AF2 RNA binding specificity using individual-nucleotide resolution crosslinking immunoprecipitation (iCLIP) in control and HNRNPA1 overexpression cells. We observed changes in the distribution of U2AF2 crosslinking sites relative to the 3'ss of alternative cassette exons but not constitutive exons upon HNRNPA1 overexpression. A subset of these events shows a concomitant increase of U2AF2 crosslinking at distal intronic regions, suggesting a shift of U2AF2 to "decoy" binding sites. Of the many noncanonical U2AF2 binding sites, Alu-derived RNA sequences represented one of the most abundant classes of HNRNPA1-dependent decoys. We propose that one way HNRNPA1 regulates exon definition is to modulate the interaction of U2AF2 with decoy or bona fide 3'ss.Item Identification and validation of genes with expression patterns inverse to multiple metastasis suppressor genes in breast cancer cell lines(Springer-Verlag, 2014-10) Marino, Natascia; Collins, Joshua W.; Shen, Changyu; Caplen, Natasha J.; Merchant, Anand S.; Gökmen-Polar, Yesim; Goswami, Chirayu P.; Hoshino, Takashi; Qian, Yongzhen; Sledge, George W.; Steeg, Patricia S.; Department of Pathology and Laboratory Medicine, IU School of MedicineMetastasis suppressor genes (MSGs) have contributed to an understanding of regulatory pathways unique to the lethal metastatic process. When re-expressed in experimental models, MSGs block cancer spread to, and colonization of distant sites without affecting primary tumor formation. Genes have been identified with expression patterns inverse to a single MSG, and found to encode functional, druggable signaling pathways. We now hypothesize that common signaling pathways mediate the effects of multiple MSGs. By gene expression profiling of human MCF7 breast carcinoma cells expressing a scrambled siRNA, or siRNAs to each of 19 validated MSGs (NME1, BRMS1, CD82, CDH1, CDH2, CDH11, CASP8, MAP2K4, MAP2K6, MAP2K7, MAPK14, GSN, ARHGDIB, AKAP12, DRG1, CD44, PEBP1, RRM1, KISS1), we identified genes whose expression was significantly opposite to at least five MSGs. Five genes were selected for further analysis: PDE5A, UGT1A, IL11RA, DNM3 and OAS1. After stable downregulation of each candidate gene in the aggressive human breast cancer cell line MDA-MB-231T, in vitro motility was significantly inhibited. Two stable clones downregulating PDE5A (phosphodiesterase 5A), an enzyme involved in the regulation of cGMP-specific signaling, exhibited no difference in cell proliferation, but reduced motility by 47 and 66 % compared to the empty vector-expressing cells (p = 0.01 and p = 0.005). In an experimental metastasis assay, two shPDE5A-MDA-MB-231T clones produced 47-62 % fewer lung metastases than shRNA-scramble expressing cells (p = 0.045 and p = 0.009 respectively). This study demonstrates that previously unrecognized genes are inversely related to the expression of multiple MSGs, contribute to aspects of metastasis, and may stand as novel therapeutic targets.Item Identification of candidate genes for alcohol preference by expression profiling of congenic rat strains(Wiley Blackwell (Blackwell Publishing), 2007-07) Carr, Lucinda G.; Kimpel, Mark W.; Liang, Tiebing; McClintick, Jeanette N.; McCall, Kevin; Morse, Melissa; Edenberg, Howard J.; Department of Medicine, IU School of MedicineBACKGROUND: A highly significant quantitative trait locus (QTL) on chromosome 4 that influenced alcohol preference was identified by analyzing crosses between the iP and iNP rats. Congenic strains in which the iP chromosome 4 QTL interval was transferred to the iNP (NP.P) exhibited the expected increase in alcohol consumption compared with the iNP background strain. This study was undertaken to identify genes in the chromosome 4 QTL interval that might contribute to the differences in alcohol consumption between the alcohol-naïve congenic and background strains. METHODS: RNA from 5 brain regions from each of 6 NP.P and 6 iNP rats was labeled and analyzed separately on an Affymetrix Rat Genome 230 2.0 microarray to look for both cis-regulated and trans-regulated genes. Expression levels were normalized using robust multi-chip average (RMA). Differential gene expression was validated using quantitative real-time polymerase chain reaction. Five individual brain regions (nucleus accumbens, frontal cortex, amygdala, hippocampus, and striatum) were analyzed to detect differential expression of genes within the introgressed QTL interval, as well as genes outside that region. To increase the power to detect differentially expressed genes, combined analyses (averaging data from the 5 discrete brain regions of each animal) were also carried out. RESULTS: Analyses within individual brain regions that focused on genes within the QTL interval detected differential expression in all 5 brain regions; a total of 35 genes were detected in at least 1 region, ranging from 6 genes in the nucleus accumbens to 22 in the frontal cortex. Analysis of the whole genome detected very few differentially expressed genes outside the QTL. Combined analysis across brain regions was more powerful. Analysis focused on the genes within the QTL interval confirmed 19 of the genes detected in individual regions and detected 15 additional genes. Whole genome analysis detected 1 differentially expressed gene outside the interval. CONCLUSIONS: Cis-regulated candidate genes for alcohol consumption were identified using microarray profiling of gene expression differences in congenic animals carrying a QTL for alcohol preference.Item Identification of genes and pathways involved in kidney renal clear cell carcinoma(Springer (Biomed Central Ltd.), 2014) Yang, William; Yoshigoe, Kenji; Qin, Xiang; Liu, Jun S.; Yang, Jack Y.; Niemierko, Andrzej; Deng, Youping; Liu, Yunlong; Dunker, A. Keith; Chen, Zhongxue; Wang, Liangjiang; Xu, Dong; Arabnia, Hamid R.; Tong, Weida; Yang, Mary Qu; Department of Medical and Molecular Genetics, IU School of MedicineBACKGROUND: Kidney Renal Clear Cell Carcinoma (KIRC) is one of fatal genitourinary diseases and accounts for most malignant kidney tumours. KIRC has been shown resistance to radiotherapy and chemotherapy. Like many types of cancers, there is no curative treatment for metastatic KIRC. Using advanced sequencing technologies, The Cancer Genome Atlas (TCGA) project of NIH/NCI-NHGRI has produced large-scale sequencing data, which provide unprecedented opportunities to reveal new molecular mechanisms of cancer. We combined differentially expressed genes, pathways and network analyses to gain new insights into the underlying molecular mechanisms of the disease development. RESULTS: Followed by the experimental design for obtaining significant genes and pathways, comprehensive analysis of 537 KIRC patients' sequencing data provided by TCGA was performed. Differentially expressed genes were obtained from the RNA-Seq data. Pathway and network analyses were performed. We identified 186 differentially expressed genes with significant p-value and large fold changes (P < 0.01, |log(FC)| > 5). The study not only confirmed a number of identified differentially expressed genes in literature reports, but also provided new findings. We performed hierarchical clustering analysis utilizing the whole genome-wide gene expressions and differentially expressed genes that were identified in this study. We revealed distinct groups of differentially expressed genes that can aid to the identification of subtypes of the cancer. The hierarchical clustering analysis based on gene expression profile and differentially expressed genes suggested four subtypes of the cancer. We found enriched distinct Gene Ontology (GO) terms associated with these groups of genes. Based on these findings, we built a support vector machine based supervised-learning classifier to predict unknown samples, and the classifier achieved high accuracy and robust classification results. In addition, we identified a number of pathways (P < 0.04) that were significantly influenced by the disease. We found that some of the identified pathways have been implicated in cancers from literatures, while others have not been reported in the cancer before. The network analysis leads to the identification of significantly disrupted pathways and associated genes involved in the disease development. Furthermore, this study can provide a viable alternative in identifying effective drug targets. CONCLUSIONS: Our study identified a set of differentially expressed genes and pathways in kidney renal clear cell carcinoma, and represents a comprehensive computational approach to analysis large-scale next-generation sequencing data. The pathway and network analyses suggested that information from distinctly expressed genes can be utilized in the identification of aberrant upstream regulators. Identification of distinctly expressed genes and altered pathways are important in effective biomarker identification for early cancer diagnosis and treatment planning. Combining differentially expressed genes with pathway and network analyses using intelligent computational approaches provide an unprecedented opportunity to identify upstream disease causal genes and effective drug targets.Item LTMG: a novel statistical modeling of transcriptional expression states in single-cell RNA-Seq data(Oxford University Press, 2019-10-10) Wan, Changlin; Chang, Wennan; Zhang, Yu; Shah, Fenil; Lu, Xiaoyu; Zang, Yong; Zhang, Anru; Cao, Sha; Fishel, Melissa L.; Ma, Qin; Zhang, Chi; Medical and Molecular Genetics, School of MedicineA key challenge in modeling single-cell RNA-seq data is to capture the diversity of gene expression states regulated by different transcriptional regulatory inputs across individual cells, which is further complicated by largely observed zero and low expressions. We developed a left truncated mixture Gaussian (LTMG) model, from the kinetic relationships of the transcriptional regulatory inputs, mRNA metabolism and abundance in single cells. LTMG infers the expression multi-modalities across single cells, meanwhile, the dropouts and low expressions are treated as left truncated. We demonstrated that LTMG has significantly better goodness of fitting on an extensive number of scRNA-seq data, comparing to three other state-of-the-art models. Our biological assumption of the low non-zero expressions, rationality of the multimodality setting, and the capability of LTMG in extracting expression states specific to cell types or functions, are validated on independent experimental data sets. A differential gene expression test and a co-regulation module identification method are further developed. We experimentally validated that our differential expression test has higher sensitivity and specificity, compared with other five popular methods. The co-regulation analysis is capable of retrieving gene co-regulation modules corresponding to perturbed transcriptional regulations. A user-friendly R package with all the analysis power is available at https://github.com/zy26/LTMGSCA.Item LtpA, a CdnL-type CarD regulator, is important for the enzootic cycle of the Lyme disease pathogen(Nature Publishing Group, 2018-07-09) Chen, Tong; Xiang, Xuwu; Xu, Haijun; Zhang, Xuechao; Zhou, Bibi; Yang, Youyun; Lou, Yongliang; Yang, X. Frank; Microbiology and Immunology, School of MedicineLittle is known about how Borrelia burgdorferi, the Lyme disease pathogen, adapts and survives in the tick vector. We previously identified a bacterial CarD N-terminal-like (CdnL) protein, LtpA (BB0355), in B. burgdorferi that is preferably expressed at lower temperatures, which is a surrogate condition mimicking the tick portion of the enzootic cycle of B. burgdorferi. CdnL-family proteins, an emerging class of bacterial RNAP-interacting transcription factors, are essential for the viability of Mycobacterium tuberculosis and Myxococcus xanthus. Previous attempts to inactivate ltpA in B. burgdorferi have not been successful. In this study, we report the construction of a ltpA mutant in the infectious strain of B. burgdorferi, strain B31-5A4NP1. Unlike CdnL in M. tuberculosis and M. xanthus, LtpA is dispensable for the viability of B. burgdorferi. However, the ltpA mutant exhibits a reduced growth rate and a cold-sensitive phenotype. We demonstrate that LtpA positively regulates 16S rRNA expression, which contributes to the growth defects in the ltpA mutant. The ltpA mutant remains capable of infecting mice, albeit with delayed infection. Additionally, the ltpA mutant produces markedly reduced spirochetal loads in ticks and was not able to infect mice via tick infection. Overall, LtpA represents a novel regulator in the CdnL family that has an important role in the enzootic cycle of B. burgdorferi.