scholarly journals Performance of gene expression analyses using de novo assembled transcripts in polyploid species

2018 ◽  
Author(s):  
Ling-Yun Chen ◽  
Diego F. Morales-Briones ◽  
Courtney N. Passow ◽  
Ya Yang
Keyword(s):  
Gene Expression ◽  
Differentially Expressed Genes ◽  
Reference Genes ◽  
De Novo ◽  
Differentially Expressed ◽  
Supplementary Information ◽  
Network Analyses ◽  
Gene Expression Analyses ◽  
Polyploidy Event ◽  
Differential Gene

AbstractMotivationQuality of gene expression analyses using de novo assembled transcripts in species experienced recent polyploidization is yet unexplored.ResultsFive plant species with various polyploidy history were used for differential gene expression (DGE) analyses. DGE analyses using putative genes inferred by Trinity performed similar to or better than Corset and Grouper in precision, but lower in sensitivity. In species that lack polyploidy event in the past few million years, DGE analyses using de novo assembled transcriptome identified 50–76% of the differentially expressed genes recovered by mapping reads to the reference genes. However, in species with more recent polyploidy event, the percentage decreased to 7–30%. In addition, 7–89% of differentially expressed genes from de novo assembly are contaminations. Gene co-expression network analyses using de novo assemblies vs. mapping to the reference genes recovered the same module that significantly correlated with treatment in one of the five species tested.Availability and ImplementationCommands and scripts used in this study are available at https://bitbucket.org/lychen83/chen_et_al_2018_benchmark_dge/; Analysis files are available at Dryad doi: [email protected] informationSupplementary data are available at Bioinformatics online

scholarly journals Performance of gene expression analyses using de novo assembled transcripts in polyploid species

2019 ◽  
Vol 35 (21) ◽  
pp. 4314-4320 ◽  
Author(s):  
Ling-Yun Chen ◽  
Diego F Morales-Briones ◽  
Courtney N Passow ◽  
Ya Yang
Keyword(s):  
Gene Expression ◽  
Reference Genes ◽  
De Novo ◽  
Supplementary Information ◽  
Polyploid Species ◽  
Network Analyses ◽  
The Past ◽  
Gene Expression Analyses ◽  
Differential Gene

Abstract Motivation Quality of gene expression analyses using de novo assembled transcripts in species that experienced recent polyploidization remains unexplored. Results Differential gene expression (DGE) analyses using putative genes inferred by Trinity, Corset and Grouper performed slightly differently across five plant species that experienced various polyploidy histories. In species that lack recent polyploidy events that occurred in the past several millions of years, DGE analyses using de novo assembled transcriptomes identified 54–82% of the differentially expressed genes recovered by mapping reads to the reference genes. However, in species that experienced more recent polyploidy events, the percentage decreased to 21–65%. Gene co-expression network analyses using de novo assemblies versus mapping to the reference genes recovered the same module that significantly correlated with treatment in one species that lacks recent polyploidization. Availability and implementation Commands and scripts used in this study are available at https://bitbucket.org/lychen83/chen_et_al_2018_benchmark_dge/; Analysis files are available at Dryad doi: 10.5061/dryad.4p6n481. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals СONSECUTIVE INTEGRATION OF AVAILABLE MICROARRAY DATA FOR ANALYSIS OF DIFFERENTIAL GENE EXPRESSION IN HUMAN PLACENTA

2021 ◽  
Vol 14 (1) ◽  
pp. 38-45
Author(s):  
O. Lykhenko ◽  
Keyword(s):  
Gene Expression ◽  
Differential Gene Expression ◽  
Differentially Expressed Genes ◽  
Human Placenta ◽  
Normal Pregnancy ◽  
Integrative Analysis ◽  
Differentially Expressed ◽  
Second Trimester ◽  
Placental Development ◽  
Differential Gene

The purpose of the study was to provide the pipeline for processing of publicly available unprocessed data on gene expression via integration and differential gene expression analysis. Data collection from open gene expression databases, normalization and integration into a single expression matrix in accordance with metadata and determination of differentially expressed genes were fulfilled. To demonstrate all stages of data processing and integrative analysis, there were used the data from gene expression in the human placenta from the first and second trimesters of normal pregnancy. The source code for the integrative analysis was written in the R programming language and publicly available as a repository on GitHub. Four clusters of functionally enriched differentially expressed genes were identified for the human placenta in the interval between the first and second trimester of pregnancy. Immune processes, developmental processes, vasculogenesis and angiogenesis, signaling and the processes associated with zinc ions varied in the considered interval between the first and second trimester of placental development. The proposed sequence of actions for integrative analysis could be applied to any data obtained by microarray technology.

scholarly journals Identification of gene expression alterations in C. elegans adr-2 mutants using high- throughput sequencing

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Jackson Townsend ◽  
Heather A. Hundley
Keyword(s):  
Gene Expression ◽  
Young Adult ◽  
Rna Editing ◽  
Differential Gene Expression ◽  
Differentially Expressed Genes ◽  
High Throughput Sequencing ◽  
Life Stage ◽  
Differentially Expressed ◽  
C Elegans ◽  
Differential Gene

Background and Hypothesis: RNA editing is one of several mechanisms regulating gene expression. One type of RNA editing, the deamination of adenosine to inosine, is carried out by ADAR enzymes. ADAR enzymes are essential for neural function and aberrant editing is implicated in various forms of neuropathology. C. elegans lacking the RNA editing enzyme, ADR-2, are viable allowing us to ascertain how loss of RNA editing affects neural gene expression. The effects of loss of adr-2 on neural gene expression will be analyzed in both the first larval (L1) and young adult stages. We hypothesize that the transcriptome will change depending on life stage and the presence of ADR-2. Methods: Three replicates of neural cells isolated from wild type and adr-2(-) L1 and young adult stage animals were obtained. Total RNA was extracted from each population and mRNA was isolated using an oligo-dT bead. The mRNA was fragmented, and reverse transcribed to generate a complentary DNA (cDNA) library. The cDNA was sequenced by a facility at Indiana University. Quality of the library was evaluated using FASTqc. DE-seq2 software evaluated the differential gene expression. Results: I examined differential gene expression in two life stages of the WT and adr-2 neural samples. After obtaining the differentially expressed genes, the portions of the transcriptome that require ADR-2 was determined. WT young adults showed increased (3715) and decreased (2504) expression of neural genes when compared to the L1 stage. Many differentially expressed genes required adr-2 (~40% of the upregulated and 78% of the downregulated genes.) In addition, some genes were uniquely altered (631 upregulated, 196 downregulated) in the absence of adr-2. Conclusion and Potential Impact: The life stage and presence of ADR-2 alter the neural transcriptome and this function changes throughout development. Future studies will determine whether these genes are altered due to the lack of RNA editing or binding by ADR-2.

scholarly journals Research and Clinical Significance of the Differentially Expressed Genes TP63 and LMO4 in Human Immunodeficiency Virus-Related Penile Squamous Cell Carcinoma

2021 ◽  
Vol 15 (2) ◽  
pp. 155798832110113
Author(s):  
Wenrui Xue ◽  
Xin Zheng ◽  
Xiaopeng Hu ◽  
Yu Zhang
Keyword(s):  
Gene Expression ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Differentially Expressed Genes ◽  
Squamous Cell ◽  
Differentially Expressed ◽  
Control Group ◽  
Go Enrichment ◽  
Differential Gene ◽  
Penile Squamous Cell Carcinoma

To study the differential gene expression and clinical significance in human immunodeficiency virus-infected individuals (HIVIIs) with penile squamous cell carcinoma. At our hospital from 2019 to 2020, we selected six samples of HIV-related penile squamous cell carcinoma for the experimental group and six samples of non-HIV-related penile squamous cell carcinoma for the control group. Transcriptome sequencing of sample mRNAs was performed by high-throughput sequencing. Differential gene expression analysis, differential Gene Ontology (GO) enrichment analysis and differential Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were carried out, and the reads per kilobase per million reads (RPKM) value was used as a measure of gene expression. A total of 2418 differentially expressed genes were obtained, of which 663 were upregulated and 1755 were downregulated (absolute value of logFC >1 and p value <.05). On the basis of the significance of the GO enrichment analysis, we found that the tumor protein p63 (TP63) gene was significantly upregulated and that the LIM domain only 4 (LMO4) gene was significantly downregulated in the experimental group compared with the control group. KEGG pathway analysis of the differentially expressed genes revealed that DNA replication was the most significant pathway associated with the upregulated genes and cell adhesion molecule (CAM) metabolism was the most significant pathway associated with the downregulated genes. The gene expression profiles of HIV-related penile squamous cell carcinoma and non-HIV-related penile squamous cell carcinoma are significantly different and involve significant GO enrichment and KEGG metabolic pathways, and this is very meaningful for the study of non-AIDS-defining cancers (NADCs). Differential expression of genes may be an important target for the prevention of penile squamous cell carcinoma in HIVIIs.

Genes influenced by MEF2C contribute to neurodevelopmental disease via gene expression changes that affect multiple types of cortical excitatory neurons

2019 ◽  
Author(s):  
Donna Cosgrove ◽  
Laura Whitton ◽  
Laura Fahey ◽  
Pilib Ó Broin ◽  
Gary Donohoe ◽  
...  
Keyword(s):  
Gene Expression ◽  
Intellectual Disability ◽  
Cognitive Function ◽  
Brain Development ◽  
Differentially Expressed Genes ◽  
De Novo ◽  
Cell Types ◽  
Differentially Expressed ◽  
Glutamatergic Neurons ◽  
Excitatory Neurons

AbstractMyocyte enhancer factor 2 C (MEF2C) is an important transcription factor during neurodevelopment. Mutation or deletion of MEF2C causes intellectual disability (ID) and common variants within MEF2C are associated with cognitive function and schizophrenia risk. We investigated if genes influenced by MEF2C during neurodevelopment are enriched for genes associated with neurodevelopmental phenotypes, and if this can be leveraged to identify biological mechanisms and individual brain cell types affected. We used a set of 1,052 genes that were differentially expressed in the adult mouse brain following early embryonic deletion of Mef2c in excitatory cortical neurons. Using GWAS data, we found these differentially expressed genes (DEGs) to be enriched for genes associated with schizophrenia, intelligence and educational attainment but not autism spectrum disorder (ASD). Using sequencing data from trios studies, we found these DEGs to be enriched for genes containing de novo mutations reported in ASD and ID, but not schizophrenia. Using single cell RNA-seq data, we identified that a number of different excitatory glutamatergic neurons in the cortex were enriched for these DEGs including deep layer pyramidal cells and cells in the retrosplenial cortex, entorhinal cortex and subiculum. These data indicate that genes influenced by MEF2C during neurodevelopment contribute to cognitive function and risk of neurodevelopmental disorders. Within excitatory neurons, common SNPs in these genes contribute to cognition and SZ risk via an effect on synaptic function based on gene ontology analysis. In contrast, rare mutations contribute to earlier onset ASD and ID via an effect on cell morphogenesis.Author SummarySchizophrenia is a complex disorder caused by many genes. Current drugs for schizophrenia are only partially effective and do not treat cognitive deficits, which are key factors for explaining disability. Here we take an individual gene identified in genetic studies of schizophrenia and cognition called MEF2C, which on its own is a very important regulator of brain development. We use data from a mouse study where MEF2C has been stopped from functioning or knocked out during brain development. The effect of that knock out has been measured when the mice reach adulthood, in the form of a set of differentially expressed genes (DEGs) from the somatosensory cortex. We found that this set of DEGs contains more genes than expected by chance that are associated with schizophrenia and cognition or contain rare new (de novo) mutations reported in autism and intellectual disability. Using gene expression data from single brain cells, we identified that a number of specific excitatory glutamatergic neurons in the cortex were enriched for these DEGs. This study provides evidence that the molecular mechanisms that underpin schizophrenia and cognitive function include disruption of cell types influenced by MEF2C.

Changes in Differential Gene and Protein Expression Patterns during Development of Cord Blood (CB) Versus Adult Peripheral Blood (APB) Monocyte (Mo) into Mature Dendritic Cells (mDC): Insight into Immaturity of CB DC Immunity.

Blood ◽  
2006 ◽  
Vol 108 (11) ◽  
pp. 5204-5204
Author(s):  
Hong Jiang ◽  
Cheryl Wade-Harris ◽  
Megan Lim ◽  
Laxmi Baxi ◽  
Mitchell S. Cairo
Keyword(s):  
Gene Expression ◽  
Differentially Expressed Genes ◽  
Developmental Stages ◽  
Expression Patterns ◽  
Oligonucleotide Microarray ◽  
Differentially Expressed ◽  
Expression Of Genes ◽  
Differential Gene ◽  
Hla Dqa1 ◽  
Antigen Presenting

Abstract It has been recognized that dysfunction of CB immune system is in part due to the immaturity of CB cellular immunity (Cairo, Blood,1997). The molecular mechanisms associated with the immaturity of CB cellular immunity including DC subset remain to be defined. The maturation status of DC greatly influences its antigen presentation capacity. Recently, we have utilized oligonucleotide microarray to demonstrate differential gene expression profiles of CB vs APB Mo (Jiang/Cairo, JI, 2004). In the current study, differential expressed genes and proteins were examined in Mo-derived CB vs. APB DC during DC developmental stages: Mo, immature DC (iDC) and mDC, by utilizing oligonucleotide microarray and proteomics. Briefly, Mo isolated from CB or APB and cultured for 8 days with GM-CSF/IL-4 (iDC) and further stimulated with LPS (mDC). Oligonucleotide microarray was carried out using U133A gene chip (Affymetrix). The representative differentially expressed genes resulted from microarray analysis were selected and analyzed by quantitative RT-PCR (Roche). The proteomic technique was conducted by liquid chromatography (LC) and mass spectrometry (MS) (Lim, Mol Cell Proteomics, 2006). The differentially expressed proteins were compared in CB vs. APB for iDC and mDC. We identified different gene expression patterns that were significantly lower in CB vs. APB in different stages during DC differentiation: Mo, iDC and mDC. These differentially expressed genes included RELA (5F), JUNB (6F), IRF-1 (3F) in Mo; CREB5 (3F), MAP7 (5F), IL1R2 (6F) in iDC; and HLA-DQA1 (4F), CD80 (3F), IRF-5 (3F) in mDC. The proteomic studies demonstrated Tyrosine Kinase Fer (12.5F), Actin regulator 3 (2.5F), Rap guanine nucleotide exchange factor 1 (2.4F) and Myeloid cell nuclear differentiation antigen (1.5F) were expressed higher in APB vs.CB iDC, while MAX binding protein MNT (5.5F), IRS2 (2.2F) and Zinc-Finger Proteins (514, 212, 462) (3–14F) were expressed higher in CB vs. APB iDC. Further, the proteomic results also indicated other Zinc-Finger Proteins (292, 221, 474) (2–5F), Fibrillin 1 precursor (2.5F) and interleukin-4 (7.7F) were expressed higher in APB vs. CB mDC. In contrast, cyclin I (3F), Rb-like protein 2 (4.35 F) and PKC theta (2F) were significantly lower in APB vs. CB DC. Moreover, the comparison of CB vs. APB DC antigen presenting activity by ELISPOT was performed and the influenza-peptide loaded CB-mDC demonstrated weaker ability to induce T cells to produce IFNg compared with APB-mDC. In summary, these differentially expressed genes in Mo (RELA, JUN) may play key roles in initiating Mo differentiation toward DC. The increased expression of genes in APB vs. CB iDC, like CREB5, IL1R2, may be involved in mediating maturation process of iDC to mDC. Lastly, the elevated expression of genes in APB vs. CB mDC, such as HLA-DQA1, CD80, IRF5 among others, may be likely to control mDC functionality as demonstrated by weaker antigen presenting activity of CB vs. APB mDC. We postulate that decreased expression of specific genes in CB vs. APB DC during DC developmental stages may in part be responsible for the lack of maturity of CB, and ultimately may partially be responsible for differential CB vs. APB innate and adaptive immunity.

scholarly journals SCORE: Smart Consensus Of RNA Expression—a consensus tool for detecting differentially expressed genes in bacteria

2020 ◽  
Author(s):  
Silver A Wolf ◽  
Lennard Epping ◽  
Sandro Andreotti ◽  
Knut Reinert ◽  
Torsten Semmler
Keyword(s):  
Differentially Expressed Genes ◽  
Current Method ◽  
Differentially Expressed ◽  
Supplementary Information ◽  
Rna Expression ◽  
Rna Seq ◽  
Bacterial Rna ◽  
Differential Gene ◽  
No Gold Standard ◽  
Selection Of

Abstract Summary RNA-sequencing (RNA-Seq) is the current method of choice for studying bacterial transcriptomes. To date, many computational pipelines have been developed to predict differentially expressed genes from RNA-Seq data, but no gold-standard has been widely accepted. We present the Snakemake-based tool Smart Consensus Of RNA Expression (SCORE) which uses a consensus approach founded on a selection of well-established tools for differential gene expression analysis. This allows SCORE to increase the overall prediction accuracy and to merge varying results into a single, human-readable output. SCORE performs all steps for the analysis of bacterial RNA-Seq data, from read preprocessing to the overrepresentation analysis of significantly associated ontologies. Development of consensus approaches like SCORE will help to streamline future RNA-Seq workflows and will fundamentally contribute to the creation of new gold-standards for the analysis of these types of data. Availability and implementation https://github.com/SiWolf/SCORE. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals ViDGER: An R package for integrative interpretation of differential gene expression results of RNA-seq data

2018 ◽  
Author(s):  
Adam McDermaid ◽  
Brandon Monier ◽  
Jing Zhao ◽  
Qin Ma
Keyword(s):  
Gene Expression ◽  
Rna Sequencing ◽  
Differential Gene Expression ◽  
Differentially Expressed Genes ◽  
R Package ◽  
Differentially Expressed ◽  
Rna Seq ◽  
Differential Gene

AbstractDifferential gene expression (DGE) is one of the most common applications of RNA-sequencing (RNA-seq) data. This process allows for the elucidation of differentially expressed genes (DEGs) across two or more conditions. Interpretation of the DGE results can be non-intuitive and time consuming due to the variety of formats based on the tool of choice and the numerous pieces of information provided in these results files. Here we present an R package, ViDGER (Visualization of Differential Gene Expression Results using R), which contains nine functions that generate information-rich visualizations for the interpretation of DGE results from three widely-used tools, Cuffdiff, DESeq2, and edgeR.

scholarly journals Alternative splicing and gene expression play contrasting roles in the parallel phenotypic evolution of a salmonid fish

2020 ◽  
Author(s):  
Arne Jacobs ◽  
Kathryn R. Elmer
Keyword(s):  
Gene Expression ◽  
Alternative Splicing ◽  
Differential Gene Expression ◽  
Differentially Expressed Genes ◽  
Adaptive Evolution ◽  
Salmonid Fish ◽  
Differentially Expressed ◽  
Molecular Processes ◽  
Regulatory Regions ◽  
Differential Gene

AbstractUnderstanding the contribution of different molecular processes to the evolution and development of divergent phenotypes is crucial for identifying the molecular routes of rapid adaptation. Here, we used RNA-seq data to compare patterns of alternative splicing and differential gene expression in a case of parallel adaptive evolution, the replicated postglacial divergence of the salmonid fish Arctic charr (Salvelinus alpinus) into benthic and pelagic ecotypes across multiple independent lakes.We found that genes that were differentially spliced and differentially expressed between the benthic and pelagic ecotypes were mostly independent (<6% overlap) and were involved in different processes. Differentially spliced genes were primarily enriched for muscle development and functioning, while differentially expressed genes were mostly involved in energy metabolism, immunity and growth. Together, these likely explain different axes of divergence between ecotypes in swimming performance and activity. Furthermore, we found that alternative splicing and gene expression are mostly controlled by independent cis-regulatory quantitative trait loci (<3.4% overlap). Cis-regulatory regions were associated with the parallel divergence in splicing (16.5% of intron clusters) and expression (6.7 - 10.1% of differentially expressed genes), indicating shared regulatory variation across ecotype pairs. Contrary to theoretical expectation, we found that differentially spliced genes tended to be highly central in regulatory networks (‘hub genes’) and were annotated to significantly more gene ontology terms compared to non-differentially spliced genes, consistent with a higher level of connectivity and pleiotropy.Together, our results suggest that the concerted regulation of alternative splicing and differential gene expression through different regulatory regions leads to the divergence of complementary phenotypes important for local adaptation. This study provides novel insights into the importance of contrasting but putatively complementary molecular processes for rapid and parallel adaptive evolution.

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