scholarly journals Disease-specific biases in alternative splicing and tissue-specific dysregulation revealed by multitissue profiling of lymphocyte gene expression in type 1 diabetes

2017 ◽  
Vol 27 (11) ◽  
pp. 1807-1815 ◽  
Author(s):  
Jeremy R.B. Newman ◽  
Ana Conesa ◽  
Matthew Mika ◽  
Felicia N. New ◽  
Suna Onengut-Gumuscu ◽  
...  
Diabetes ◽  
2012 ◽  
Vol 61 (5) ◽  
pp. 1281-1290 ◽  
Author(s):  
Katharine M. Irvine ◽  
Patricia Gallego ◽  
Xiaoyu An ◽  
Shannon E. Best ◽  
Gethin Thomas ◽  
...  

2021 ◽  
Author(s):  
Jian Lin ◽  
Yuanhua Lu ◽  
Bizhou Wang ◽  
Ping Jiao ◽  
Jie Ma

Abstract Background Type 1 diabetes mellitus (T1DM) is a chronic autoimmune disease caused by severe loss of pancreatic β cells. Immune cells are key mediators of β cell destruction. This study attempted to investigate the role of immune cells and immune-related genes in the occurrence and development of T1DM. Methods The raw gene expression profile of the samples from 12 T1DM patients and 10 normal controls was obtained from Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified by Limma package in R. The least absolute shrinkage and selection operator (LASSO) - support vector machines (SVM) were used to screen the hub genes. CIBERSORT algorithm was used to identify the different immune cells in distribution between T1DM and normal samples. Correlation of the hub genes and immune cells was analyzed by Spearman, and gene-GO-BP and gene-pathway interaction networks were constructed by Cytoscape plug-in ClueGO. Receiver operating characteristic (ROC) curves were used to assess diagnostic value of genes in T1DM. Results The 50 immune-related DEGs were obtained between the T1DM and normal samples. Then, the 50 immune-related DEGs were further screened to obtain the 5 hub genes. CIBERSORT analysis revealed that the distribution of plasma cells, resting mast cells, resting NK cells and neutrophils had significant difference between T1DM and normal samples. Natural cytotoxicity triggering receptor 3 (NCR3) was significantly related to the activated NK cells, M0 macrophages, monocytes, resting NK cells, and resting memory CD4+ T cells. Moreover, tumor necrosis factor (TNF) was significantly associated with naive B cell and naive CD4+ T cell. NCR3 [Area under curve (AUC) = 0.918] possessed a higher accuracy than TNF (AUC = 0.763) in diagnosis of T1DM. Conclusions The immune-related genes (NCR3 and TNF) and immune cells (NK cells) may play a vital regulatory role in the occurrence and development of T1DM, which possibly provide new ideas and potential targets for the immunotherapy of diabetes mellitus (DM).


2020 ◽  
Author(s):  
Shufa Yang ◽  
Chenghong Yin ◽  
Yan Liu ◽  
Taifeng Zhuang

Abstract BackgroundHuman amniotic fluid (AF) cells are commonly used in prenatal diagnosis. The AF cell-free mRNA (cfRNA) derived from necrotic or apoptotic cells of fetus may provide feasible marker of organ development and fetal malformation. Analysis of gene co-expression network will help to annotate AF cfRNA gene variations in fetal diseases.MethodsDatasets of amniotic fluid free RNA were downloaded from the Gene Expression Omnibus database. Co-expressed modules based on normal fetus AF cfRNA transcriptome were established via Weighted Gene Co-expression Network Analysis. The relationship between modules and tissues were set up via tissue-specific gene expression analysis of genes in modules. Differential expressed genes in Down syndrome (DS), Edwards syndrome (ES), and Turner syndrome (TS) were analyzed via linear models implemented in the limma package. Gene Ontology (GO) analysis of modular specific differential expressed genes for these three syndrome fetus was performed separately. Based on relationship of GO terms, GO graph of all enriched GO terms were constructed. The associated enriched GO terms in GO graph were considered as the same subset. Numbers of GO terms of the same subset with diseases and modules were calculated.ResultsA total of 22 co-expressed modules were constructed. Most of co-expressed module eigengenes showed no correlation with gestation weeks. Probe sets with higher expression values showed significant clustering tendencies. Dominant tissues and modules were different for different modules and tissues respectively through analysis of tissue-specific genes distribution in modules. The total numbers of enriched GO terms in six major modules were related to diseases severity for ES, DS, and TS. Disease-specific modules for ES, DS, and TS were detected in relation to biological processes through GO analysis. Differential expressed genes in disease-specific module were identified for DS, ES, and TS.ConclusionsThe gene co-expression network for functional classification provides a potential tool for annotating AF cfRNA variations in fetal diseases.


2020 ◽  
Vol 45 (1) ◽  
pp. 22-28
Author(s):  
Marta Fichna ◽  
Magdalena Żurawek ◽  
Klaudia Bogusz-Górna ◽  
Piotr Małecki ◽  
Elżbieta Niechciał ◽  
...  

Genetics ◽  
2019 ◽  
Vol 212 (3) ◽  
pp. 931-951 ◽  
Author(s):  
Kasuen Kotagama ◽  
Anna L. Schorr ◽  
Hannah S. Steber ◽  
Marco Mangone

MicroRNAs (miRNAs) are known to modulate gene expression, but their activity at the tissue-specific level remains largely uncharacterized. To study their contribution to tissue-specific gene expression, we developed novel tools to profile putative miRNA targets in the Caenorhabditis elegans intestine and body muscle. We validated many previously described interactions and identified ∼3500 novel targets. Many of the candidate miRNA targets curated are known to modulate the functions of their respective tissues. Within our data sets we observed a disparity in the use of miRNA-based gene regulation between the intestine and body muscle. The intestine contained significantly more putative miRNA targets than the body muscle highlighting its transcriptional complexity. We detected an unexpected enrichment of RNA-binding proteins targeted by miRNA in both tissues, with a notable abundance of RNA splicing factors. We developed in vivo genetic tools to validate and further study three RNA splicing factors identified as putative miRNA targets in our study (asd-2, hrp-2, and smu-2), and show that these factors indeed contain functional miRNA regulatory elements in their 3′UTRs that are able to repress their expression in the intestine. In addition, the alternative splicing pattern of their respective downstream targets (unc-60, unc-52, lin-10, and ret-1) is dysregulated when the miRNA pathway is disrupted. A reannotation of the transcriptome data in C. elegans strains that are deficient in the miRNA pathway from past studies supports and expands on our results. This study highlights an unexpected role for miRNAs in modulating tissue-specific gene isoforms, where post-transcriptional regulation of RNA splicing factors associates with tissue-specific alternative splicing.


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