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Zhelyazkova M, Yordanova R, Mihaylov I, Tsonev S, Vassilev D. In silico discovering relationship between bacteriophages and antimicrobial resistance. BIOTECHNOL BIOTEC EQ 2023. [DOI: 10.1080/13102818.2022.2151378] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
Affiliation(s)
- Maya Zhelyazkova
- Faculty of Mathematics and Informatics, Department of Probability, Operations Research and Statistics, Sofia University St. Kliment Ohridski, Sofia, Bulgaria
| | - Roumyana Yordanova
- Faculty of Science, Department of Mathematics, Hokkaido University, Sapporo, Japan
- Department of Informatics modeling, Bulgarian Academy of Sciences, Institute of Mathematics and Informatics, Sofia, Bulgaria
| | - Iliyan Mihaylov
- Faculty of Mathematics and Informatics, Department of Information Technologies, Sofia University St. Kliment Ohridski, Sofia, Bulgaria
| | - Stefan Tsonev
- Department of Functional Genetics, Abiotic and Biotic Stress, AgroBioInstitute, Agricultural Academy, Sofia, Bulgaria
| | - Dimitar Vassilev
- Faculty of Mathematics and Informatics, Department of Computational Informatics, Sofia University St. Kliment Ohridski, Sofia, Bulgaria
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Habiba U, Sugino H, Yordanova R, Ise K, Tanei ZI, Ishida Y, Tanikawa S, Terasaka S, Sato KI, Kamoshima Y, Katoh M, Nagane M, Shibahara J, Tsuda M, Tanaka S. Loss of H3K27 trimethylation is frequent in IDH1-R132H but not in non-canonical IDH1/2 mutated and 1p/19q codeleted oligodendroglioma: a Japanese cohort study. Acta Neuropathol Commun 2021; 9:95. [PMID: 34020723 PMCID: PMC8138926 DOI: 10.1186/s40478-021-01194-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Accepted: 05/06/2021] [Indexed: 11/28/2022] Open
Abstract
Oligodendrogliomas are defined by mutation in isocitrate dehydrogenase (NADP(+)) (IDH)1/2 genes and chromosome 1p/19q codeletion. World Health Organisation diagnosis endorses testing for 1p/19q codeletion to distinguish IDH mutant (Mut) oligodendrogliomas from astrocytomas because these gliomas require different treatments and they have different outcomes. Several methods have been used to identify 1p/19q status; however, these techniques are not routinely available and require substantial infrastructure investment. Two recent studies reported reduced immunostaining for trimethylation at lysine 27 on histone H3 (H3K27me3) in IDH Mut 1p/19q codeleted oligodendroglioma. However, the specificity of H3K27me3 immunostaining in this setting is controversial. Therefore, we developed an easy-to-implement immunohistochemical surrogate for IDH Mut glioma subclassification and evaluated a validated adult glioma cohort. We screened 145 adult glioma cases, consisting of 45 IDH Mut and 1p/19q codeleted oligodendrogliomas, 30 IDH Mut astrocytomas, 16 IDH wild-type (Wt) astrocytomas, and 54 IDH Wt glioblastomas (GBMs). We compared immunostaining with DNA sequencing and fluorescent in situ hybridization analysis and assessed differences in H3K27me3 staining between oligodendroglial and astrocytic lineages and between IDH1-R132H and non-canonical (non-R132H) IDH1/2 Mut oligodendroglioma. A loss of H3K27me3 was observed in 36/40 (90%) of IDH1-R132H Mut oligodendroglioma. In contrast, loss of H3K27me3 was never seen in IDH1-R132L or IDH2-mutated 1p/19q codeleted oligodendrogliomas. IDH Mut astrocytoma, IDH Wt astrocytoma and GBM showed preserved nuclear staining in 87%, 94%, and 91% of cases, respectively. A high recursive partitioning model predicted probability score (0.9835) indicated that the loss of H3K27me3 is frequent to IDH1-R132H Mut oligodendroglioma. Our results demonstrate H3K27me3 immunohistochemical evaluation to be a cost-effective and reliable method for defining 1p/19q codeletion along with IDH1-R132H and ATRX immunostaining, even in the absence of 1p/19q testing.
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Zhelyazkova M, Yordanova R, Mihaylov I, Kirov S, Tsonev S, Danko D, Mason C, Vassilev D. Origin Sample Prediction and Spatial Modeling of Antimicrobial Resistance in Metagenomic Sequencing Data. Front Genet 2021; 12:642991. [PMID: 33763122 PMCID: PMC7983949 DOI: 10.3389/fgene.2021.642991] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Accepted: 02/02/2021] [Indexed: 12/18/2022] Open
Abstract
The steady elaboration of the Metagenomic and Metadesign of Subways and Urban Biomes (MetaSUB) international consortium project raises important new questions about the origin, variation, and antimicrobial resistance of the collected samples. CAMDA (Critical Assessment of Massive Data Analysis, http://camda.info/) forum organizes annual challenges where different bioinformatics and statistical approaches are tested on samples collected around the world for bacterial classification and prediction of geographical origin. This work proposes a method which not only predicts the locations of unknown samples, but also estimates the relative risk of antimicrobial resistance through spatial modeling. We introduce a new component in the standard analysis as we apply a Bayesian spatial convolution model which accounts for spatial structure of the data as defined by the longitude and latitude of the samples and assess the relative risk of antimicrobial resistance taxa across regions which is relevant to public health. We can then use the estimated relative risk as a new measure for antimicrobial resistance. We also compare the performance of several machine learning methods, such as Gradient Boosting Machine, Random Forest, and Neural Network to predict the geographical origin of the mystery samples. All three methods show consistent results with some superiority of Random Forest classifier. In our future work we can consider a broader class of spatial models and incorporate covariates related to the environment and climate profiles of the samples to achieve more reliable estimation of the relative risk related to antimicrobial resistance.
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Affiliation(s)
- Maya Zhelyazkova
- Faculty of Mathematics and Informatics, Sofia University St. Kliment Ohridski, Sofia, Bulgaria
| | - Roumyana Yordanova
- Department of Mathematics, Hokkaido University, Sapporo, Japan.,Bulgarian Academy of Sciences, Institute of Mathematics and Informatics, Sofia, Bulgaria
| | - Iliyan Mihaylov
- Faculty of Mathematics and Informatics, Sofia University St. Kliment Ohridski, Sofia, Bulgaria
| | - Stefan Kirov
- Bristol-Myers Squibb, Pennington, NJ, United States
| | - Stefan Tsonev
- Department of Molecular Genetics, AgroBioInstitute, Sofia, Bulgaria
| | - David Danko
- Department of Computational Informatics, Weill Cornell Medical College, New York, NY, United States
| | | | - Dimitar Vassilev
- Faculty of Mathematics and Informatics, Sofia University St. Kliment Ohridski, Sofia, Bulgaria
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Ivanov I, Atkinson D, Litvinenko I, Angelova L, Andonova S, Mumdjiev H, Pacheva I, Panova M, Yordanova R, Belovejdov V, Petrova A, Bosheva M, Shmilev T, Savov A, Jordanova A. Pontocerebellar hypoplasia type 1 for the neuropediatrician: Genotype-phenotype correlations and diagnostic guidelines based on new cases and overview of the literature. Eur J Paediatr Neurol 2018; 22:674-681. [PMID: 29656927 DOI: 10.1016/j.ejpn.2018.03.011] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/21/2017] [Revised: 03/20/2018] [Accepted: 03/27/2018] [Indexed: 10/17/2022]
Abstract
Pontocerebellar hypoplasia type 1 (PCH1) is a major cause of non-5q spinal muscular atrophy (SMA). We screened 128 SMN1-negative SMA patients from Bulgaria for a frequent mutation -p.G31A in EXOSC3, and performed a literature review of all genetically verified PCH1 cases. Homozygous p.G31A/EXOSC3 mutation was identified in 14 Roma patients, representing three fourths of all our SMN1-negative Roma SMA cases. The phenotype of the p.G31A/EXOSC3 homozygotes was compared to the clinical presentation of all reported to date genetically verified PCH1 cases. Signs of antenatal onset of disease present at birth were common in all PCH1 sub-types except in the homozygous p.D132A/EXOSC3 patients. The PCH1sub-types with early death (between ages 1 day and 17 months), seen in patients with p.G31A/EXOSC3 or SLC25A46 mutations have a SMA type 1-like clinical presentation but with global developmental delay, visual and hearing impairment, with or without microcephaly, nystagmus and optic atrophy. Mutations with milder presentation (homozygous p.D132A/EXOSC3 or VRK1) may display additionally signs of upper motor neuron impairment, dystonia or ataxia and die at age between 5 and 18 years. Other EXOSC3 mutations and EXOSC8 cases are intermediate - SMA type 1-like presentation, spasticity (mostly in EXOSC8) and death between 3 months and 5 years. There is no correlation between neurological onset and duration of life. We add marble-like skin and congenital laryngeal stridor as features of PCH1. We show that imaging signs of cerebellar and pontine hypoplasia may be missing early in infancy. EMG signs of anterior horn neuronopathy may be missing in PCH1 patients with SLC25A46 mutations. Thus, there is considerable phenotypic variability in PCH1, with some cases being more SMA-like, than PCH-like. Detailed clinical evaluation and ethnicity background may guide genetic testing and subsequent genetic counseling.
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Affiliation(s)
- I Ivanov
- Department of Pediatrics, St. George University Hospital, Medical University-Plovdiv, Plovdiv, Bulgaria.
| | - D Atkinson
- VIB Center for Molecular Neurology, University of Antwerp, Belgium.
| | - I Litvinenko
- Department of Pediatrics, SBALDB "Prof. D-r Ivan Mitev", Medical University-Sofia, Sofia, Bulgaria.
| | - L Angelova
- Department of Medical Genetics, University Hospital "St. Marina", Medical University of Varna, Varna, Bulgaria.
| | - S Andonova
- National Genetic Laboratory, Maichin Dom University Hospital, Sofia, Bulgaria.
| | - H Mumdjiev
- Department of Neonatology, Prof. Stoyan Kirkovich University Hospital, Medical Faculty of Tracian University, Stara Zagora, Bulgaria.
| | - I Pacheva
- Department of Pediatrics, St. George University Hospital, Medical University-Plovdiv, Plovdiv, Bulgaria.
| | - M Panova
- Department of Pediatrics, St. George University Hospital, Medical University-Plovdiv, Plovdiv, Bulgaria.
| | - R Yordanova
- Department of Pediatrics, St. George University Hospital, Medical University-Plovdiv, Plovdiv, Bulgaria.
| | - V Belovejdov
- Department of Pathology, St. George University Hospital, Medical University-Plovdiv, Plovdiv, Bulgaria.
| | - A Petrova
- Department of Radiology, St. George University Hospital, Medical University-Plovdiv, Plovdiv, Bulgaria.
| | - M Bosheva
- Department of Pediatrics, St. George University Hospital, Medical University-Plovdiv, Plovdiv, Bulgaria.
| | - T Shmilev
- Department of Pediatrics, St. George University Hospital, Medical University-Plovdiv, Plovdiv, Bulgaria.
| | - A Savov
- National Genetic Laboratory, Maichin Dom University Hospital, Sofia, Bulgaria.
| | - A Jordanova
- VIB Center for Molecular Neurology, University of Antwerp, Belgium; Molecular Medicine Center, Department of Medical Chemistry and Biochemistry, Medical University-Sofia, Sofia, Bulgaria.
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Ha T, Swanson D, Larouche M, Glenn R, Weeden D, Zhang P, Hamre K, Langston M, Phillips C, Song M, Ouyang Z, Chesler E, Duvvurru S, Yordanova R, Cui Y, Campbell K, Ricker G, Phillips C, Homayouni R, Goldowitz D. CbGRiTS: cerebellar gene regulation in time and space. Dev Biol 2014; 397:18-30. [PMID: 25446528 DOI: 10.1016/j.ydbio.2014.09.032] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2014] [Revised: 08/23/2014] [Accepted: 09/27/2014] [Indexed: 01/09/2023]
Abstract
The mammalian CNS is one of the most complex biological systems to understand at the molecular level. The temporal information from time series transcriptome analysis can serve as a potent source of associative information between developmental processes and regulatory genes. Here, we introduce a new transcriptome database called, Cerebellar Gene Regulation in Time and Space (CbGRiTS). This dataset is populated with transcriptome data across embryonic and postnatal development from two standard mouse strains, C57BL/6J and DBA/2J, several recombinant inbred lines and cerebellar mutant strains. Users can evaluate expression profiles across cerebellar development in a deep time series with graphical interfaces for data exploration and link-out to anatomical expression databases. We present three analytical approaches that take advantage of specific aspects of the time series for transcriptome analysis. We demonstrate the use of CbGRiTS dataset as a community resource to explore patterns of gene expression and develop hypotheses concerning gene regulatory networks in brain development.
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Affiliation(s)
- Thomas Ha
- Centre for Molecular Medicine and Therapeutics, Child and Family Research Institute, Department of Medical Genetics, University of British Columbia, 950 West 28th Avenue, Vancouver, BC, Canada V5Z 4H4
| | - Douglas Swanson
- Centre for Molecular Medicine and Therapeutics, Child and Family Research Institute, Department of Medical Genetics, University of British Columbia, 950 West 28th Avenue, Vancouver, BC, Canada V5Z 4H4
| | - Matt Larouche
- Centre for Molecular Medicine and Therapeutics, Child and Family Research Institute, Department of Medical Genetics, University of British Columbia, 950 West 28th Avenue, Vancouver, BC, Canada V5Z 4H4
| | - Randy Glenn
- Centre for Molecular Medicine and Therapeutics, Child and Family Research Institute, Department of Medical Genetics, University of British Columbia, 950 West 28th Avenue, Vancouver, BC, Canada V5Z 4H4
| | - Dave Weeden
- Centre for Molecular Medicine and Therapeutics, Child and Family Research Institute, Department of Medical Genetics, University of British Columbia, 950 West 28th Avenue, Vancouver, BC, Canada V5Z 4H4
| | - Peter Zhang
- Centre for Molecular Medicine and Therapeutics, Child and Family Research Institute, Department of Medical Genetics, University of British Columbia, 950 West 28th Avenue, Vancouver, BC, Canada V5Z 4H4
| | - Kristin Hamre
- Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Michael Langston
- Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, TN, USA
| | - Charles Phillips
- Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, TN, USA
| | - Mingzhou Song
- Department of Computer Science, New Mexico State University, Las Cruces, NM, USA
| | - Zhengyu Ouyang
- Department of Computer Science, New Mexico State University, Las Cruces, NM, USA
| | | | | | | | - Yan Cui
- Department of Molecular Science, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Kate Campbell
- Centre for Molecular Medicine and Therapeutics, Child and Family Research Institute, Department of Medical Genetics, University of British Columbia, 950 West 28th Avenue, Vancouver, BC, Canada V5Z 4H4
| | - Greg Ricker
- Department of Biology, Bowdoin College, Brunswick, ME, USA
| | - Carey Phillips
- Department of Biology, Bowdoin College, Brunswick, ME, USA
| | - Ramin Homayouni
- Bioinformatics Program, Department of Biology, University of Memphis, Memphis, TN, USA
| | - Dan Goldowitz
- Centre for Molecular Medicine and Therapeutics, Child and Family Research Institute, Department of Medical Genetics, University of British Columbia, 950 West 28th Avenue, Vancouver, BC, Canada V5Z 4H4.
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Yordanova R, Maslenkova L, Paunova S, Popova L. Sensitivity of Photosynthetic Apparatus of Pea Plants to Heavy Metal Stress. BIOTECHNOL BIOTEC EQ 2014. [DOI: 10.1080/13102818.2009.10818436] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022] Open
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Korman AJ, Engelhardt J, Shahabi V, Yordanova R, Henning K, Chen T, Selby M. Role of the immunoglobulin constant region in the antitumor activity of antibodies to cytotoxic T-lymphocyte antigen-4 (CTLA-4). J Clin Oncol 2013. [DOI: 10.1200/jco.2013.31.15_suppl.9055] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
9055 Background: Anti-CTLA-4 therapy enhances antitumor T-cell responses by both cell-intrinsic and cell-extrinsic mechanisms. Effector T-cell (Teff) activation is increased directly by interfering with CTLA-4-B7 interactions that negatively regulate T cells and by interfering with CTLA-4 expressed on regulatory T cells (Tregs), which function to inhibit immune responses. To analyze in greater detail the mechanism of action of anti-CTLA-4 antibodies (Abs), we examined the role of the immunoglobulin constant region in the antitumor activity of anti-CTLA-4 Abs in mouse tumor models. Methods: The activity of anti-CTLA-4 Abs with different mouse IgG constant regions were compared in several mouse tumor models, and intratumoral and peripheral T cells were analyzed by FACS. DNA samples from 488 patients with metastatic melanoma who received ipilimumab in a phase III clinical trial, MDX010-20, were analyzed for polymorphisms in the IgG fragment c receptor (FcR) at FCGR3A (V158F) and FCGR2A (H131R) loci. Results: In subcutaneous MC38 and CT26 colon tumor models, an anti-CTLA-4 Ab containing the mouse IgG2a constant region exhibited enhanced antitumor activity compared to an anti-CTLA-4 Ab containing the IgG2b constant region, while anti-CTLA-4 Abs containing mouse IgG1 or a mutated mouse IgG1 D265A constant region showed no activity. Anti-CTLA-4-IgG2a caused a dramatic reduction of Tregs at the tumor site that resulted in a greater Teff/Treg ratio. In contrast, all isotypes resulted in expansion of Tregs in the periphery. These results point to an important role for FcR in the action of anti-CTLA-4 Abs. In patients from study MDX010-20, there was no association between the 2 FcR polymorphisms (FCGR3A and FCGR2A) and overall survival. Conclusions: These preclinical studies reveal a novel dual activity of anti-CTLA-4 Abs consisting of intratumoral reduction of Tregs together with activation of Teff cells. This effect is mediated by the constant region and is presumably due to antibody-dependent cellular cytotoxicity. The data suggest that FcR-bearing cells at the tumor site, as well as the presence of intratumoral Tregs, may be important factors in the antitumor activity of anti-CTLA-4 Abs.
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Orozco LD, Bennett BJ, Farber CR, Ghazalpour A, Pan C, Che N, Wen P, Qi HX, Mutukulu A, Siemers N, Neuhaus I, Yordanova R, Gargalovic P, Pellegrini M, Kirchgessner T, Lusis AJ. Unraveling inflammatory responses using systems genetics and gene-environment interactions in macrophages. Cell 2013; 151:658-70. [PMID: 23101632 DOI: 10.1016/j.cell.2012.08.043] [Citation(s) in RCA: 90] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2012] [Revised: 06/06/2012] [Accepted: 08/15/2012] [Indexed: 10/27/2022]
Abstract
Many common diseases have an important inflammatory component mediated in part by macrophages. Here we used a systems genetics strategy to examine the role of common genetic variation in macrophage responses to inflammatory stimuli. We examined genome-wide transcript levels in macrophages from 92 strains of the Hybrid Mouse Diversity Panel. We exposed macrophages to control media, bacterial lipopolysaccharide (LPS), or oxidized phospholipids. We performed association mapping under each condition and identified several thousand expression quantitative trait loci (eQTL), gene-by-environment interactions, and eQTL "hot spots" that specifically control LPS responses. We used siRNA knockdown of candidate genes to validate an eQTL hot spot in chromosome 8 and identified the gene 2310061C15Rik as a regulator of inflammatory responses in macrophages. We have created a public database where the data presented here can be used as a resource for understanding many common inflammatory traits that are modeled in the mouse and for the dissection of regulatory relationships between genes.
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Affiliation(s)
- Luz D Orozco
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA 90095, USA.
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Abstract
Gene set enrichment analysis for analyzing large profiling and screening experiments can reveal unifying biological schemes based on previously accumulated knowledge represented as “gene sets”. Most of the existing implementations use a fixed fold-change or P value cutoff to generate regulated gene lists. However, the threshold selection in most cases is arbitrary, and has a significant effect on the test outcome and interpretation of the experiment. We developed a new gene set enrichment analysis method, ie, FDR-FET, which dynamically optimizes the threshold choice and improves the sensitivity and selectivity of gene set enrichment analysis. The procedure translates experimental results into a series of regulated gene lists at multiple false discovery rate (FDR) cutoffs, and computes the P value of the overrepresentation of a gene set using a Fisher’s exact test (FET) in each of these gene lists. The lowest P value is retained to represent the significance of the gene set. We also implemented improved methods to define a more relevant global reference set for the FET. We demonstrate the validity of the method using a published microarray study of three protease inhibitors of the human immunodeficiency virus and compare the results with those from other popular gene set enrichment analysis algorithms. Our results show that combining FDR with multiple cutoffs allows us to control the error while retaining genes that increase information content. We conclude that FDR-FET can selectively identify significant affected biological processes. Our method can be used for any user-generated gene list in the area of transcriptome, proteome, and other biological and scientific applications.
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Affiliation(s)
- Rui-Ru Ji
- Applied Genomics, Research and Development, Bristol-Myers Squibb, Pennington, NJ, USA
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Ghazalpour A, Bennett B, Petyuk VA, Orozco L, Hagopian R, Mungrue IN, Farber CR, Sinsheimer J, Kang HM, Furlotte N, Park CC, Wen PZ, Brewer H, Weitz K, Camp DG, Pan C, Yordanova R, Neuhaus I, Tilford C, Siemers N, Gargalovic P, Eskin E, Kirchgessner T, Smith DJ, Smith RD, Lusis AJ. Comparative analysis of proteome and transcriptome variation in mouse. PLoS Genet 2011; 7:e1001393. [PMID: 21695224 PMCID: PMC3111477 DOI: 10.1371/journal.pgen.1001393] [Citation(s) in RCA: 437] [Impact Index Per Article: 33.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2010] [Accepted: 05/10/2011] [Indexed: 12/11/2022] Open
Abstract
The relationships between the levels of transcripts and the levels of the proteins they encode have not been examined comprehensively in mammals, although previous work in plants and yeast suggest a surprisingly modest correlation. We have examined this issue using a genetic approach in which natural variations were used to perturb both transcript levels and protein levels among inbred strains of mice. We quantified over 5,000 peptides and over 22,000 transcripts in livers of 97 inbred and recombinant inbred strains and focused on the 7,185 most heritable transcripts and 486 most reliable proteins. The transcript levels were quantified by microarray analysis in three replicates and the proteins were quantified by Liquid Chromatography–Mass Spectrometry using O(18)-reference-based isotope labeling approach. We show that the levels of transcripts and proteins correlate significantly for only about half of the genes tested, with an average correlation of 0.27, and the correlations of transcripts and proteins varied depending on the cellular location and biological function of the gene. We examined technical and biological factors that could contribute to the modest correlation. For example, differential splicing clearly affects the analyses for certain genes; but, based on deep sequencing, this does not substantially contribute to the overall estimate of the correlation. We also employed genome-wide association analyses to map loci controlling both transcript and protein levels. Surprisingly, little overlap was observed between the protein- and transcript-mapped loci. We have typed numerous clinically relevant traits among the strains, including adiposity, lipoprotein levels, and tissue parameters. Using correlation analysis, we found that a low number of clinical trait relationships are preserved between the protein and mRNA gene products and that the majority of such relationships are specific to either the protein levels or transcript levels. Surprisingly, transcript levels were more strongly correlated with clinical traits than protein levels. In light of the widespread use of high-throughput technologies in both clinical and basic research, the results presented have practical as well as basic implications. An old dogma in biology states that, in every cell, the flow of biological information is from DNA to RNA to proteins and that the latter act as a working force to determine the organism's phenotype. This model predicts that changes in DNA that affect the clinical phenotype should also similarly change the cellular levels of RNA and protein levels. In this report, we test this prediction by looking at the concordance between DNA variation in population of mouse inbred strains, the RNA and protein variation in the liver tissue of these mice, and variation in metabolic phenotypes. We show that the relationship between various biological traits is not simple and that there is relatively little concordance of RNA levels and the corresponding protein levels in response to DNA perturbations. In addition, we also find that, surprisingly, metabolic traits correlate better to RNA levels than to protein levels. In light of current efforts in searching for the molecular bases of disease susceptibility in humans, our findings highlight the complexity of information flow that underlies clinical outcomes.
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Affiliation(s)
- Anatole Ghazalpour
- Department of Medicine/Division of Cardiology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, United States of America.
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Abstract
Differences in clinical phenotypes between the sexes are well documented and have their roots in differential gene expression. While sex has a major effect on gene expression, transcription is also influenced by complex interactions between individual genetic variation and environmental stimuli. In this study, we sought to understand how genetic variation affects sex-related differences in liver gene expression by performing genetic mapping of genomewide liver mRNA expression data in a genetically defined population of naive male and female mice from C57BL/6J, DBA/2J, B6D2F1, and 37 C57BL/6J x DBA/2J (BXD) recombinant inbred strains. As expected, we found that many genes important to xenobiotic metabolism and other important pathways exhibit sexually dimorphic expression. We also performed gene expression quantitative trait locus mapping in this panel and report that the most significant loci that appear to regulate a larger number of genes than expected by chance are largely sex independent. Importantly, we found that the degree of correlation within gene expression networks differs substantially between the sexes. Finally, we compare our results to a recently released human liver gene expression data set and report on important similarities in sexually dimorphic liver gene expression between mouse and human. This study enhances our understanding of sex differences at the genome level and between species, as well as increasing our knowledge of the molecular underpinnings of sex differences in responses to xenobiotics.
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Affiliation(s)
- Daniel M Gatti
- Department of Environmental Sciences and Engineering, University of North Carolina, Chapel Hill, North Carolina 27599, USA
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Hanumegowda UM, Wenke G, Regueiro-Ren A, Yordanova R, Corradi JP, Adams SP. Phospholipidosis as a Function of Basicity, Lipophilicity, and Volume of Distribution of Compounds. Chem Res Toxicol 2010; 23:749-55. [DOI: 10.1021/tx9003825] [Citation(s) in RCA: 80] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Umesh M. Hanumegowda
- Departments of Discovery Toxicology, Discovery Analytical Sciences, Discovery Chemistry, and Bioinformatics, Bristol-Myers Squibb Research and Development, 5 Research Parkway, Wallingford, Connecticut 06492
| | - Gottfried Wenke
- Departments of Discovery Toxicology, Discovery Analytical Sciences, Discovery Chemistry, and Bioinformatics, Bristol-Myers Squibb Research and Development, 5 Research Parkway, Wallingford, Connecticut 06492
| | - Alicia Regueiro-Ren
- Departments of Discovery Toxicology, Discovery Analytical Sciences, Discovery Chemistry, and Bioinformatics, Bristol-Myers Squibb Research and Development, 5 Research Parkway, Wallingford, Connecticut 06492
| | - Roumyana Yordanova
- Departments of Discovery Toxicology, Discovery Analytical Sciences, Discovery Chemistry, and Bioinformatics, Bristol-Myers Squibb Research and Development, 5 Research Parkway, Wallingford, Connecticut 06492
| | - John P. Corradi
- Departments of Discovery Toxicology, Discovery Analytical Sciences, Discovery Chemistry, and Bioinformatics, Bristol-Myers Squibb Research and Development, 5 Research Parkway, Wallingford, Connecticut 06492
| | - Stephen P. Adams
- Departments of Discovery Toxicology, Discovery Analytical Sciences, Discovery Chemistry, and Bioinformatics, Bristol-Myers Squibb Research and Development, 5 Research Parkway, Wallingford, Connecticut 06492
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Romanoski CE, Lee S, Kim MJ, Ingram-Drake L, Plaisier CL, Yordanova R, Tilford C, Guan B, He A, Gargalovic PS, Kirchgessner TG, Berliner JA, Lusis AJ. Systems genetics analysis of gene-by-environment interactions in human cells. Am J Hum Genet 2010; 86:399-410. [PMID: 20170901 DOI: 10.1016/j.ajhg.2010.02.002] [Citation(s) in RCA: 84] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2009] [Revised: 01/21/2010] [Accepted: 02/02/2010] [Indexed: 01/15/2023] Open
Abstract
Gene by environment (GxE) interactions are clearly important in many human diseases, but they have proven to be difficult to study on a molecular level. We report genetic analysis of thousands of transcript abundance traits in human primary endothelial cell (EC) lines in response to proinflammatory oxidized phospholipids implicated in cardiovascular disease. Of the 59 most regulated transcripts, approximately one-third showed evidence of GxE interactions. The interactions resulted primarily from effects of distal-, trans-acting loci, but a striking example of a local-GxE interaction was also observed for FGD6. Some of the distal interactions were validated by siRNA knockdown experiments, including a locus involved in the regulation of multiple transcripts involved in the ER stress pathway. Our findings add to the understanding of the overall architecture of complex human traits and are consistent with the possibility that GxE interactions are responsible, in part, for the failure of association studies to more fully explain common disease variation.
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Bennett BJ, Farber CR, Orozco L, Kang HM, Ghazalpour A, Siemers N, Neubauer M, Neuhaus I, Yordanova R, Guan B, Truong A, Yang WP, He A, Kayne P, Gargalovic P, Kirchgessner T, Pan C, Castellani LW, Kostem E, Furlotte N, Drake TA, Eskin E, Lusis AJ. A high-resolution association mapping panel for the dissection of complex traits in mice. Genome Res 2010; 20:281-90. [PMID: 20054062 DOI: 10.1101/gr.099234.109] [Citation(s) in RCA: 251] [Impact Index Per Article: 17.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Systems genetics relies on common genetic variants to elucidate biologic networks contributing to complex disease-related phenotypes. Mice are ideal model organisms for such approaches, but linkage analysis has been only modestly successful due to low mapping resolution. Association analysis in mice has the potential of much better resolution, but it is confounded by population structure and inadequate power to map traits that explain less than 10% of the variance, typical of mouse quantitative trait loci (QTL). We report a novel strategy for association mapping that combines classic inbred strains for mapping resolution and recombinant inbred strains for mapping power. Using a mixed model algorithm to correct for population structure, we validate the approach by mapping over 2500 cis-expression QTL with a resolution an order of magnitude narrower than traditional QTL analysis. We also report the fine mapping of metabolic traits such as plasma lipids. This resource, termed the Hybrid Mouse Diversity Panel, makes possible the integration of multiple data sets and should prove useful for systems-based approaches to complex traits and studies of gene-by-environment interactions.
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Affiliation(s)
- Brian J Bennett
- Department of Medicine/Division of Cardiology, David Geffen School of Medicine, University of California, Los Angeles, California 90095, USA
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