HIV-associated nephropathy: Protocol and rationale for an exploratory genotype-phenotype study in a sub-Saharan African population

Background HIV-positive persons of African descent are disproportionately affected by chronic kidney disease (CKD). Deterioration to end-stage kidney disease (ESKD) also occurs in this population at a higher frequency. There remains a lot to learn about the genetic susceptibility to CKD in HIV positive patients, and the pathophysiology of progression to ESKD. Objectives We will conduct an exploratory genotype-phenotype study in HIV-positive persons with CKD in Aminu Kano Teaching Hospital, Nigeria, to determine blood-based differential gene expression biomarkers in different kidney risk groups according to the KDIGO 2012 criteria. Methods We will consecutively screen 150 HIV-positive adults (≥18 years of age) attending the HIV clinic of Aminu Kano Teaching Hospital, Kano, Nigeria, for CKD based on proteinuria and elevation of estimated glomerular filtration rate. Among these, two separate groups of 16 eligible participants each (n = 32) will be selected in the four (4) KDIGO 2012 kidney risk categories. The groups will be matched for age, sex, viral suppression level and antiretroviral (ARV) regimen. In the first group (n = 16), we will determine differential gene expression markers in peripheral blood mononuclear cells using mRNA-sequencing (RNA-Seq). We will validate the differential expression markers in the second group (n = 16) using reverse transcription quantitative polymerase chain reaction (RT-qPCR). Using a systems-based approach, we will construct, visualize and analyze gene-gene interaction networks to determine the potential biological roles of identified differential expression markers based on published literature and publicly available databases. Results Our exploratory study will provide valuable information on the potential roles of differential expression biomarkers in the pathophysiology of HIV-associated kidney disease by identifying novel biomarkers in different risk categories of CKD in a sub-Saharan African population. The results of this study will provide the basis for population-based genome-wide association studies to guide future personalized medicine approaches. Conclusion Validated biomarkers can be potential targets for the development of stage-specific therapeutic interventions, an essential paradigm in precision medicine.

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The Western Diet Regulates Hippocampal Microvascular Gene Expression: An Integrated Genomic Analyses in Female Mice

Scientific Reports ◽

10.1038/s41598-019-55533-9 ◽

2019 ◽

Vol 9 (1) ◽

Cited By ~ 4

Author(s):

Saivageethi Nuthikattu ◽

Dragan Milenkovic ◽

John Rutledge ◽

Amparo Villablanca

Keyword(s):

Gene Expression ◽

Transcription Factors ◽

Differential Expression ◽

Differential Gene Expression ◽

Gene Networks ◽

Molecular Mechanisms ◽

Western Diet ◽

Protein Coding ◽

Female Mice ◽

Differential Gene

AbstractHyperlipidemia is a risk factor for dementia, and chronic consumption of a Western Diet (WD) is associated with cognitive impairment. However, the molecular mechanisms underlying the development of microvascular disease in the memory centers of the brain are poorly understood. This pilot study investigated the nutrigenomic pathways by which the WD regulates gene expression in hippocampal brain microvessels of female mice. Five-week-old female low-density lipoprotein receptor deficient (LDL-R−/−) and C57BL/6J wild type (WT) mice were fed a chow or WD for 8 weeks. Metabolics for lipids, glucose and insulin were determined. Differential gene expression, gene networks and pathways, transcription factors, and non-protein coding RNAs were evaluated by genome-wide microarray and bioinformatics analysis of laser captured hippocampal microvessels. The WD resulted in differential expression of 2,412 genes. The majority of differential gene expression was attributable to differential regulation of cell signaling proteins and their transcription factors, approximately 7% was attributable to differential expression of miRNAs, and a lesser proportion was due to other non-protein coding RNAs, primarily long non-coding RNAs (lncRNAs) and small nucleolar RNAs (snoRNAs) not previously described to be modified by the WD in females. Our findings revealed that chronic consumption of the WD resulted in integrated multilevel molecular regulation of the hippocampal microvasculature of female mice and may provide one of the mechanisms underlying vascular dementia.

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RankerGUI: A Computational Framework to Compare Differential Gene Expression Profiles Using Rank Based Statistics

International Journal of Molecular Sciences ◽

10.3390/ijms20236098 ◽

2019 ◽

Vol 20 (23) ◽

pp. 6098 ◽

Cited By ~ 1

Author(s):

Amarinder Singh Thind ◽

Kumar Parijat Tripathi ◽

Mario Rosario Guarracino

Keyword(s):

Gene Expression ◽

Differential Expression ◽

Differential Gene Expression ◽

Web Application ◽

Cellular Response ◽

Expression Profiles ◽

Expression Patterns ◽

Gene Expression Profiles ◽

Experimental Conditions ◽

Differential Gene

The comparison of high throughput gene expression datasets obtained from different experimental conditions is a challenging task. It provides an opportunity to explore the cellular response to various biological events such as disease, environmental conditions, and drugs. There is a need for tools that allow the integration and analysis of such data. We developed the “RankerGUI pipeline”, a user-friendly web application for the biological community. It allows users to use various rank based statistical approaches for the comparison of full differential gene expression profiles between the same or different biological states obtained from different sources. The pipeline modules are an integration of various open-source packages, a few of which are modified for extended functionality. The main modules include rank rank hypergeometric overlap, enriched rank rank hypergeometric overlap and distance calculations. Additionally, preprocessing steps such as merging differential expression profiles of multiple independent studies can be added before running the main modules. Output plots show the strength, pattern, and trends among complete differential expression profiles. In this paper, we describe the various modules and functionalities of the developed pipeline. We also present a case study that demonstrates how the pipeline can be used for the comparison of differential expression profiles obtained from multiple platforms’ data of the Gene Expression Omnibus. Using these comparisons, we investigate gene expression patterns in kidney and lung cancers.

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Defining cell identity beyond the premise of differential gene expression

Cell Regeneration ◽

10.1186/s13619-021-00083-7 ◽

2021 ◽

Vol 10 (1) ◽

Author(s):

Hani Jieun Kim ◽

Patrick P. L. Tam ◽

Pengyi Yang

Keyword(s):

Gene Expression ◽

Differential Expression ◽

Cell Fate ◽

Differential Gene Expression ◽

Cell Types ◽

Cell Identity ◽

Gene Transcripts ◽

Differential Gene ◽

Biological Attributes

AbstractIdentifying genes that define cell identity is a requisite step for characterising cell types and cell states and predicting cell fate choices. By far, the most widely used approach for this task is based on differential expression (DE) of genes, whereby the shift of mean expression are used as the primary statistics for identifying gene transcripts that are specific to cell types and states. While DE-based methods are useful for pinpointing genes that discriminate cell types, their reliance on measuring difference in mean expression may not reflect the biological attributes of cell identity genes. Here, we highlight the quest for non-DE methods and provide an overview of these methods and their applications to identify genes that define cell identity and functionality.

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The SF3b Splicing Complex Regulates DNA Damage Response in Acute Lymphoblastic Leukemia

Blood ◽

10.1182/blood-2019-124787 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 1237-1237 ◽

Cited By ~ 1

Author(s):

Shalini Sankar ◽

Miriam Guillen Navarro ◽

Frida Ponthan ◽

Simon Bomken ◽

Sirintra Nakjang ◽

...

Keyword(s):

Gene Expression ◽

Dna Damage ◽

Differential Expression ◽

Differential Gene Expression ◽

Research Funding ◽

Gene Set Enrichment Analysis ◽

Rna Seq ◽

Self Renewal ◽

Strand Breaks ◽

Differential Gene

To identify potential regulators of propagation and self-renewal of Acute Lymphoblastic Leukaemia (ALL), we performed an explorative genome-wide RNAi screen followed by CRISPR ex vivo and in vivo validation screens in the t(4;11)-positive ALL cell line SEM. These screens identified the splicing factor PHF5A as a crucial component of the leukemic program. PHF5A is a subunit of the SF3b protein complex, which directs alternative splicing by binding to the branchpoint of pre-mRNA. Mutations in members of this complex including SF3B1 have been implicated in several haematological malignancies. Functional perturbation experiments demonstrated that PHF5A depletion impairs proliferation, viability and clonogenicity in a range of ALL and AML cell lines strongly suggesting that PHF5A is required for leukemic propagation and self-renewal. To identify genetic programs affected by PHF5A inhibition, we performed RNA-seq followed by analysis of differential gene expression and splicing events. We identified 473 genes with differential expression upon PHF5A knockdown. In addition, we performed in-depth analysis of splicing patterns by examining both differential exon/intron usage and exon junction formation. These analyses demonstrated that loss of PHF5A affects splicing of more than 2500 genes with exon skipping and intron retention being the most frequent splicing events. In order to identify processes and pathways affected by PHF5A, we performed gene set enrichment analysis (GSEA) on both differential expression and splicing. While gene sets associated with RNA processing including splicing, turnover and translation were enriched in both data sets, the differential gene expression signature was also linked to DNA repair processes including base excision, mismatch and homologous recombination repair. In line with these findings, knockdown of either PHF5A or its partner protein SF3B1 induced DNA strand breaks as indicated by comet assay and increased y-H2AX levels. Furthermore, both PHF5A and SF3B1 depletion sensitized ALL cells towards the DNA crosslinking agent mitomycin C. Closer inspection of RNA-seq datasets revealed reduced FANCD2 expression and skipping of exon 22 associated with impaired mono-ubiquitination of the FANCD2 protein as a consequence of PHF5A and SF3B1 knockdown. Furthermore, expression of RAD51, a key component of double strand break repair, also decreased upon PHF5A and SF3B1 knockdown. Notably, in vitro pharmacological inhibition of SF3b complex activity using H3B-8800 (or Pladienolide B) showed a very similar effect on FANCD2 expression, and ubiquitination as well as decrease of RAD51 and an increase in y-H2AX levels on a dose and time-dependent manner. This strongly suggests a mechanistic link between impaired RNA splicing and the repair of DNA double-strand breaks. These combined data show that leukemic cells are highly dependent on a functional SF3b splicing complex. Interference with its function results in DNA damage and also sensitizes towards DNA damaging agents pointing towards a possible benefit of the combined application of inhibitors targeting the SF3b complex with more conventional chemotherapy. Disclosures Ponthan: Epistem Ltd: Employment. Zwaan:Sanofi: Consultancy; Incyte: Consultancy; BMS: Research Funding; Roche: Consultancy; Janssen: Consultancy; Daiichi Sankyo: Consultancy; Servier: Consultancy; Jazz Pharmaceuticals: Other: Travel support; Pfizer: Research Funding; Celgene: Consultancy, Research Funding. Vormoor:Abbvie (uncompensated): Consultancy, Honoraria; Novartis: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Roche/Genentech: Consultancy, Honoraria, Research Funding; AstraZeneca: Research Funding.

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Integrative, normalization-insusceptible statistical analysis of RNA-Seq data, with improved differential expression and unbiased downstream functional analysis

Briefings in Bioinformatics ◽

10.1093/bib/bbaa156 ◽

2020 ◽

Author(s):

Dionysios Fanidis ◽

Panagiotis Moulos

Keyword(s):

Gene Expression ◽

Statistical Analysis ◽

Differential Expression ◽

Differential Gene Expression ◽

Expression Patterns ◽

Superior Performance ◽

P Value ◽

Rna Seq ◽

Daily Lives ◽

Differential Gene

Abstract The study of differential gene expression patterns through RNA-Seq comprises a routine task in the daily lives of molecular bioscientists, who produce vast amounts of data requiring proper management and analysis. Despite widespread use, there are still no widely accepted golden standards for the normalization and statistical analysis of RNA-Seq data, and critical biases, such as gene lengths and problems in the detection of certain types of molecules, remain largely unaddressed. Stimulated by these unmet needs and the lack of in-depth research into the potential of combinatorial methods to enhance the analysis of differential gene expression, we had previously introduced the PANDORA P-value combination algorithm while presenting evidence for PANDORA’s superior performance in optimizing the tradeoff between precision and sensitivity. In this article, we present the next generation of the algorithm along with a more in-depth investigation of its capabilities to effectively analyze RNA-Seq data. In particular, we show that PANDORA-reported lists of differentially expressed genes are unaffected by biases introduced by different normalization methods, while, at the same time, they comprise a reliable input option for downstream pathway analysis. Additionally, PANDORA outperforms other methods in detecting differential expression patterns in certain transcript types, including long non-coding RNAs.

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Differential gene expression is associated with degeneration of mating-type chromosomes in the absence of sexual antagonism

10.1101/626291 ◽

2019 ◽

Author(s):

Wen-Juan Ma ◽

Fantin Carpentier ◽

Tatiana Giraud ◽

Michael Hood

Keyword(s):

Gene Expression ◽

Differential Expression ◽

Differential Gene Expression ◽

Mating Type ◽

Mating Types ◽

Antagonistic Selection ◽

Expression Of Genes ◽

Sexually Antagonistic Selection ◽

Differential Gene ◽

Anther Smut

AbstractIn animals and plants, differential expression of genes on sex chromosomes is widespread and it is usually considered to result from sexually antagonistic selection; however differential expression can also be caused by asymmetrical sequence degeneration in non-recombining sex chromosomes, which has been very little studied. The anther-smut fungus Microbotryum lychnidis-dioicae is ideal to investigate the extent to which differential gene expression is associated with sequence degeneration because: 1) separate haploid cultures of opposite mating types help identify differential expression, 2) its mating-type chromosomes display multiple evolutionary strata reflecting successive events of gene linkage to the mating-type loci, and 3) antagonistic selection is unlikely between isogamous haploid mating types. We therefore tested the hypothesis that differential gene expression between mating types resulted from sequence degeneration. We found that genes showing differential expression between haploid mating types were enriched only on the oldest evolutionary strata of the mating-type chromosomes and were associated with multiple signatures of sequence degeneration. We found that differential expression between mating types was associated with elevated differences between alleles in non-synonymous substitution rates, indels and premature stop codons, transposable element insertions, and altered intron and GC content. Our findings strongly suggest that degenerative mutations are important in the evolution of differential expression in non-recombining regions. Our results are relevant for a broad range of taxa where mating compatibility or sex is determined by genes located in large regions of recombination suppression, showing that differential expression should not be taken as necessarily arising from antagonistic selection.Author SummaryDifferences between males and females, from morphology to behavior and physiology, are considered to largely reflect differential expression of genes that maximize fitness benefits relative to costs that are specific to one sex. However, there is an unexplored alternative to such ‘sexually antagonistic selection’ to explain differential expression. Reproductive compatibility is often determined by genes located in large non-recombining chromosomal regions, where degenerative mutations are expected to accumulate and may separately affect the expression of alternate alleles of genes. We tested the role of genetic degeneration in determining differential expression between the isogamous haploid mating types of the anther-smut fungus, Microbotryum lychnidis-dioicae, where sexually antagonistic selection is not a confounding factor. We show that differentially expressed genes are highly enriched in the non-recombining mating-type chromosomes, and that they are associated with various forms of degenerative mutations, some of which indicate that the less expressed allele suffers greater mutational effects. Our finding of the role for degenerative mutations in the evolution of differential expression is relevant for a broad range of organisms where reproductive compatibility or sex is determined by genes in regions of suppressed recombination, and shows that differential expression should not be taken as necessarily arising from antagonistic selection.

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Assessment of the differential gene expression in anthracnose treated seedlings of yellow lupin

Doklady of the National Academy of Sciences of Belarus ◽

10.29235/1561-8323-2021-65-3-330-336 ◽

2021 ◽

Vol 65 (3) ◽

pp. 330-336

Author(s):

E. N. Sysoliatin ◽

V. S. Anokhina ◽

N. V. Anisimova ◽

O. G. Babak ◽

A. V. Kilchevsky

Keyword(s):

Gene Expression ◽

Differential Expression ◽

Differential Gene Expression ◽

Genetic Determinants ◽

Yellow Lupin ◽

Expression Of Genes ◽

Differential Gene ◽

Colletotrichum Lupini ◽

Yellow Lupine ◽

Differential Expression Of Genes

Seedlings of yellow lupine treated with Colletotrichum lupini isolate were studied by the method of SRAP-analysis with the purpose to assess the differential expression of genes. As a result, the PCR fragment corresponding to tolerant seedlings was found. The genetic determinants found are likely involved in the control of the resistance (tolerance) of lupine plants to anthracnose.

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Differential gene expression in pulmonary artery endothelial cells exposed to sickle cell plasma

Physiological Genomics ◽

10.1152/physiolgenomics.00246.2004 ◽

2005 ◽

Vol 21 (3) ◽

pp. 293-298 ◽

Cited By ~ 15

Author(s):

Elizabeth S. Klings ◽

Surinder Safaya ◽

Adeboye H. Adewoye ◽

Adam Odhiambo ◽

Garrett Frampton ◽

...

Keyword(s):

Gene Expression ◽

Steady State ◽

Pulmonary Artery ◽

Differential Expression ◽

Differential Gene Expression ◽

Sickle Cell ◽

Cholesterol Biosynthesis ◽

Cellular Stress Response ◽

Acute Chest Syndrome ◽

Differential Gene

Clinical variability in sickle cell disease (SCD) suggests a role for extra-erythrocytic factors in the pathogenesis of vasoocclusion. We hypothesized that endothelial cell (EC) dysfunction, one possible modifier of disease variability, results from induction of phenotypic changes by circulating factors. Accordingly, we analyzed gene expression in cultured human pulmonary artery ECs (HPAEC) exposed to plasma from 1) sickle acute chest syndrome (ACS) patients, 2) SCD patients at steady state, 3) normal volunteers, and 4) serum-free media, using whole genome microarrays (U133A-B GeneChip, Affymetrix). Data were analyzed by Bayesian analysis of differential gene expression (BADGE). Differential expression was defined by the probability of >1.5 fold change in signal intensity greater than 0.999 and a predicted score of 70–100, measured by cross-validation. Compared with normal plasma, plasma from SCD patients (steady state) resulted in differential expression of 50 genes in HPAEC. Of these genes, molecules involved in cholesterol biosynthesis and lipid transport, the cellular stress response, and extracellular matrix proteins were most prominent. Another 58 genes were differentially expressed in HPAEC exposed to plasma from ACS patients. The pattern of altered gene expression suggests that plasma from SCD patients induces an EC phenotype which is anti-apoptotic and favors cholesterol biosynthesis. An altered EC phenotype elicited by SCD plasma may contribute to the pathogenesis of sickle vasoocclusion.

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Do count-based differential expression methods perform poorly when genes are expressed in only one condition?

10.1101/017673 ◽

2015 ◽

Author(s):

Xiaobei Zhou ◽

Mark D Robinson

Keyword(s):

Gene Expression ◽

Differential Expression ◽

Differential Gene Expression ◽

Expression Analysis ◽

Gene Expression Analysis ◽

Comprehensive Evaluation ◽

Rna Seq ◽

D Genome ◽

Differential Gene Expression Analysis ◽

Differential Gene

A correspondence with respect to: Comprehensive evaluation of differential gene expression analysis methods for RNA-seq data Rapaport F, Khanin R, Liang Y, Pirun M, Krek A, Zumbo P, Mason CE, Socci ND and Betel D, Genome Biol 2013, 14:R95

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Differential gene expression in liposarcoma: Insight into pathways for dedifferentiation?

Journal of Clinical Oncology ◽

10.1200/jco.2012.30.15_suppl.10048 ◽

2012 ◽

Vol 30 (15_suppl) ◽

pp. 10048-10048

Author(s):

Dale Han ◽

Gregory C Bloom ◽

Marilyn M Bui ◽

Steven Enkemann ◽

Hideko Yamauchi ◽

...

Keyword(s):

Gene Expression ◽

Lipid Metabolism ◽

Network Analysis ◽

Differential Expression ◽

Differential Gene Expression ◽

Gene Networks ◽

Expression Patterns ◽

Differential Regulation ◽

Gene Expression Patterns ◽

Differential Gene

10048 Background: Liposarcoma (LPS) dedifferentiation signifies conversion to a clinically aggressive phenotype, but the biologic processes required for this change have not been determined. We describe differential gene expression patterns between well-differentiated (WD) and dedifferentiated (DD) tumors to determine pathways involved in LPS dedifferentiation. Methods: From 1999 to 2006, 121 fatty tumors were resected at a single institution. Twenty tumors, consisting of atypical lipomatous tumors (ALT), WD LPS or DD LPS, were randomly selected and clinicopathologic characteristics were retrospectively reviewed. Gene expression profiling was performed on extracted RNA using the Affymetrix GeneChip platform. Differentially expressed genes were obtained and gene network analysis was done using GeneGO by MetaCore. Results: Median age was 59 years and 70% of cases were male. WD tumors, consisting of 3 ALT and 6 WD LPS, were compared with 11 DD LPS. After a median follow-up of 64 months, 7 patients had died of whom 6 had DD LPS. DD histology was associated with lower overall survival (p<0.05). Significance Analysis of Microarrays for WD tumors vs. DD LPS using a 0% false discovery rate showed differential expression of 188 genes. Network analysis of genes from WD tumors vs. DD LPS showed significant (p<0.001) differential regulation of glucose-activated transcription factor ChREBP (carbohydrate response element binding protein), a key element involved in lipogenesis, gluconeogenesis and glycolysis. There was also significant differential regulation of insulin signaling, PI3K-dependent and PKA signal transduction pathways and of amino acid, fatty acid and glucose metabolism pathways (p<0.05). These pathways, based on Gene Ontology cellular processes, mapped to gene networks primarily involved in lipid metabolism (p<0.05). Conclusions: Differential expression of genes involved in lipid metabolism networks is seen in DD LPS and changes in lipid metabolism may be associated with dedifferentiation. These differential gene expression patterns may help identify fatty tumors potentially at risk for progressing to a malignant or DD state and provide prognostic factors and therapeutic targets for patients with LPS.

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