<HashMap><database>biostudies-arrayexpress</database><scores/><additional><omics_type>Metabolomics</omics_type><omics_type>Unknown</omics_type><omics_type>Transcriptomics</omics_type><omics_type>Genomics</omics_type><omics_type>Proteomics</omics_type><submitter>Suad AlFadhli</submitter><study_type>transcription profiling by array</study_type><organism>Homo sapiens</organism><species>Homo sapiens</species><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/E-GEOD-62764</full_dataset_link><description>Genome-wide alternative splice analysis of RNA from lupus and its severe form lupus nephritis We aimed to explore the genome-wide peripheral blood transcriptome of lupus (SLE) and its severe form lupus nephritis (LN) cases compared to healthy subjects (HC) using high density Affymetrix Human Exon1.0.ST arrays. Analysis revealed 15 splice variants that are differentially expressed between SLE/HC and 99 variants between LN/HC (pâ&#x89;¤0.05,SI>orâ&#x89;¤0.5,Benjamin Hochberg-False discovery rate correction). Comparison between LN/SLE revealed 7 variants that are differentially expressed with pâ&#x89;¤0.05,SI>0.5,Benjamin Hochberg-FDR correction. Pathway analysis of differentially spliced genes revealed 11 significant pathways in SLE and 12 in LN (p&lt;0.05). Analysis of peripheral blood transcriptome revealed signature causative genes that are alternatively spliced, signifying their clinical relevance in the pathophysiology of disease. The extent of differential splicing was found to be higher in LN than in SLE, signifying the need for further in-depth research in the same domain. Present study is the first to reveal the significance of alternative variants in susceptibility to SLE and LN. We analyzed blood from 11 female subjects (5 lupus, 3 lupus nephritis and 3 healthy control) using the Affymetrix Human Exon 1.0 ST platform. Array data was processed by Alt Analyze and Genespring software. No techinical replicates were performed. One of the outiler sample (HC2)  was excluded from further analysis.</description><repository>biostudies-arrayexpress</repository><sample_protocol>Hybridization - Samples were hybridized with GeneChip Human Exon 1.0 ST Arrays (Affymetrix) and scanned at the Kuwait University Research Core Facility.</sample_protocol><sample_protocol>Labeling - Single-stranded cDNA was generated from the amplified cRNA with the WT cDNA Synthesis Kit (Affymetrix) and then fragmented and labeled with the WT Terminal Labeling Kit (Affymetrix).</sample_protocol><sample_protocol>Growth Protocol - Blood samples were collected from patients and healthy subjects in EDTA treated tubes and placed on ice.</sample_protocol><sample_protocol>Scaning - Arrays were scanned using the Affymetrix GeneChipÂ® Scanner 3000 7G (Affymetrix, Santa Clara, USA), following manufacture's protocol.</sample_protocol><sample_protocol>Nucleic Acid Extraction - RNA was extracted from 2 ml of whole blood using QIAampÂ® RNA Blood Mini kit (Qiagen, Germany) following the manufactureâ&#x80;&#x99;s protocol. Extracted RNA was further purified using DNase (Qiagen) to remove potential genomic DNA contamination. RNA integrity was determined by Agilent Bioanalyzer 2100 (Agilent, CA, USA). Total RNA samples with a RNA integrity number (RIN) greater than 7 were used. RNA (100ng) from each sample was processed using Ambion expression kit (Life technologies, USA).</sample_protocol><figure_sub>MIAME Score</figure_sub><figure_sub>Organization</figure_sub><figure_sub>Assays and Data</figure_sub><figure_sub>Processed Data</figure_sub><figure_sub>MAGE-TAB Files</figure_sub><figure_sub>Array Designs</figure_sub><pubmed_authors>Rasheeba Nizam</pubmed_authors><pubmed_authors>Suad AlFadhli</pubmed_authors><data_protocol>Data Transformation - Data analysis was carried out using GeneSpring 12.5GX (Agilent) software. Data quality was evaluated by Principle component analysis (PCA) and any outlier sample was identified and removed. Normalization was carried out using Robust Multi-array Average (RMA) method on core probsets and baseline to median summarization was performed. At exon level, only probesets characterized by detection above background signal (DABG) p value &lt;0.05 in atleast 50% of the samples in either group were accepted for subsequent analysis. Alternate splicing events between patients and control subjects were characterized by â&#x80;&#x9c;Splice index (SI) modelâ&#x80;&#x9d; (Affymerix Inc., 2006, Gardina et al., 2006). It is represented as the log ratio of the gene normalized intensity (NI) between the two tested sample groups. NI in turn indicates the ratio of exon-level probe set expression to gene-level transcript cluster expression. To identify the significant alternatively spliced genes, splicing ANOVA with Benjamini and Hochberg false discovery rate (FDR) correction was employed on gene normalized intensities of the tested sample groups. True positives with a p â&#x89;¤0.05, SI 0.05 and Fold change (FC)>1 were considered as alternatively spliced. affymetrix-algorithm-name = rma-exon-all : dabg affymetrix-algorithm-version = 1.0 program-name = Expression Console program-version = 1.1.2800.19935 ID_REF =  VALUE = RMA expression value derived from Expression Console software; All-exon analysis DETECTION P-VALUE =</data_protocol></additional><is_claimable>false</is_claimable><name>Genome-wide peripheral blood transcriptome analysis of Arab female Lupus and Lupus nephritis</name><description>Genome-wide alternative splice analysis of RNA from lupus and its severe form lupus nephritis We aimed to explore the genome-wide peripheral blood transcriptome of lupus (SLE) and its severe form lupus nephritis (LN) cases compared to healthy subjects (HC) using high density Affymetrix Human Exon1.0.ST arrays. Analysis revealed 15 splice variants that are differentially expressed between SLE/HC and 99 variants between LN/HC (pâ&#x89;¤0.05,SI>orâ&#x89;¤0.5,Benjamin Hochberg-False discovery rate correction). Comparison between LN/SLE revealed 7 variants that are differentially expressed with pâ&#x89;¤0.05,SI>0.5,Benjamin Hochberg-FDR correction. Pathway analysis of differentially spliced genes revealed 11 significant pathways in SLE and 12 in LN (p&lt;0.05). Analysis of peripheral blood transcriptome revealed signature causative genes that are alternatively spliced, signifying their clinical relevance in the pathophysiology of disease. The extent of differential splicing was found to be higher in LN than in SLE, signifying the need for further in-depth research in the same domain. Present study is the first to reveal the significance of alternative variants in susceptibility to SLE and LN. We analyzed blood from 11 female subjects (5 lupus, 3 lupus nephritis and 3 healthy control) using the Affymetrix Human Exon 1.0 ST platform. Array data was processed by Alt Analyze and Genespring software. No techinical replicates were performed. One of the outiler sample (HC2)  was excluded from further analysis.</description><dates><release>2016-01-06T00:00:00Z</release><modification>2023-09-21T11:12:38.385Z</modification><creation>2022-02-02T21:22:11.212Z</creation></dates><accession>E-GEOD-62764</accession><cross_references><GEO>GSE62764</GEO><EFO>EFO_0002768</EFO></cross_references></HashMap>