Rhinovirus infection induces distinct transcriptome profiles in polarized human macrophages

Infections with rhinovirus (RV) cause asthma exacerbations. Recent studies suggest that macrophages play a role in asthmatic airway inflammation and the innate immune response to RV infection. Macrophages exhibit phenotypes based on surface markers and gene expression. We hypothesized that macrophage polarization state alters gene expression in response to RV infection. Cells were derived from human peripheral blood derived monocytes. M1 and M2 polarization was carried out by using IFN-γ and IL-4, respectively, and RNA was extracted for Affymetrix Human Gene ST2.1 exon arrays. Selected genes were validated by quantitative (q)PCR. Treatment of nonactivated (M0) macrophages with IFN-γ and IL-4 induced the expression of 252 and 153 distinct genes, respectively, including previously-identified M1 and M2 markers. RV infection of M0 macrophages induced upregulation of 232 genes; pathway analysis showed significant overrepresentation of genes involved in IFN-α/β signaling and cytokine signaling in the immune system. RV infection induced differential expression of 195 distinct genes in M1-like macrophages but only seven distinct genes in M2-like-polarized cells. In a secondary analysis, comparison between M0-, RV-infected, and M1-like-polarized, RV-infected macrophages revealed differential expression of 227 genes including those associated with asthma and its exacerbation. qPCR demonstrated increased expression of CCL8, CXCL10, TNFSF10, TNFSF18, IL6, NOD2, and GSDMD and reduced expression of VNN1, AGO1, and AGO2. Together, these data show that, in contrast to M2-like-polarized macrophages, gene expression of M1-like macrophages is highly regulated by RV.

Comparison of RNA-seq and Microarray Platforms for Splice Event Detection using a Cross-Platform Algorithm

RNA-seq is a reference technology for determining alternative splicing at genome-wide level. Exon arrays remain widely used for the analysis of gene expression, but show poor validation rate with regard to splicing events. Commercial arrays that include probes within exon junctions have been developed in order to overcome this problem.We compare the performance of RNA-seq (Illumina HiSeq) and junction arrays (Affymetrix Human Transcriptome array) for the analysis of transcript splicing events. Three different breast cancer cell lines were treated with CX-4945, a drug that severely affects splicing. To enable a direct comparison of the two platforms, we adapted EventPointer, an algorithm that detects and labels alternative splicing events using junction arrays, to work also on RNA-seq data. Common results and discrepancies between the technologies were validated and/or resolved by over 200 PCR experiments.As might be expected, RNA-seq appears superior in cases where the technologies disagree, and is able to discover novel splicing events beyond the limitations of physical probe-sets. We observe a high degree of coherence between the two technologies, however, with correlation of EventPointer results over 0.90. Through decimation, the detection power of the junction arrays is equivalent to RNA-seq with up to 60 million reads. Our results suggest, therefore, that exon-junction arrays are a viable alternative to RNA-seq for detection of alternative splicing events when focusing on well-described transcriptional regions.

Muscle developmental defects in heterogeneous nuclear Ribonucleoprotein A1 knockout mice

Heterogeneous ribonucleoprotein A1 (hnRNP A1) is crucial for regulating alternative splicing. Its integrated function within an organism has not, however, been identified. We generated hnRNP A1 knockout mice to study the role of hnRNP A1 in vivo . The knockout mice, hnRNP A1 −/− , showed embryonic lethality because of muscle developmental defects. The blood pressure and heart rate of the heterozygous mice were higher than those of the wild-type mice, indicating heart function defects. We performed mouse exon arrays to study the muscle development mechanism. The processes regulated by hnRNP A1 included cell adhesion and muscle contraction. The expression levels of muscle development-related genes in hnRNP A1 +/− mice were significantly different from those in wild-type mice, as detected using qRT-PCR. We further confirmed the alternative splicing patterns of muscle development-related genes including mef2c , lrrfip1 , usp28 and abcc9 . Alternative mRNA isoforms of these genes were increased in hnRNP A1 +/− mice compared with wild-type mice. Furthermore, we revealed that the functionally similar hnRNP A2/B1 did not compensate for the expression of hnRNP A1 in organisms. In summary, our study demonstrated that hnRNP A1 plays a critical and irreplaceable role in embryonic muscle development by regulating the expression and alternative splicing of muscle-related genes.

A genome-wide search for epigenetically regulated genes in zebra finch using MethylCap-seq and RNA-seq

Learning and memory formation are known to require dynamic CpG (de)methylation and gene expression changes. Here, we aimed at establishing a genome-wide DNA methylation map of the zebra finch genome, a model organism in neuroscience, as well as identifying putatively epigenetically regulated genes. RNA- and MethylCap-seq experiments were performed on two zebra finch cell lines in presence or absence of 5-aza-2′-deoxycytidine induced demethylation. First, the MethylCap-seq methodology was validated in zebra finch by comparison with RRBS-generated data. To assess the influence of (variable) methylation on gene expression, RNA-seq experiments were performed as well. Comparison of RNA-seq and MethylCap-seq results showed that at least 357 of the 3,457 AZA-upregulated genes are putatively regulated by methylation in the promoter region, for which a pathway analysis showed remarkable enrichment for neurological networks. A subset of genes was validated using Exon Arrays, quantitative RT-PCR and CpG pyrosequencing on bisulfite-treated samples. To our knowledge, this study provides the first genome-wide DNA methylation map of the zebra finch genome as well as a comprehensive set of genes of which transcription is under putative methylation control.

Integrated data analysis reveals uterine leiomyoma subtypes with distinct driver pathways and biomarkers

Uterine leiomyomas are common benign smooth muscle tumors that impose a major burden on women’s health. Recent sequencing studies have revealed recurrent and mutually exclusive mutations in leiomyomas, suggesting the involvement of molecularly distinct pathways. In this study, we explored transcriptional differences among leiomyomas harboring different genetic drivers, including high mobility group AT-hook 2 (HMGA2) rearrangements, mediator complex subunit 12 (MED12) mutations, biallelic inactivation of fumarate hydratase (FH), and collagen, type IV, alpha 5 and collagen, type IV, alpha 6 (COL4A5-COL4A6) deletions. We also explored the transcriptional consequences of 7q22, 22q, and 1p deletions, aiming to identify possible target genes. We investigated 94 leiomyomas and 60 corresponding myometrial tissues using exon arrays, whole genome sequencing, and SNP arrays. This integrative approach revealed subtype-specific expression changes in key driver pathways, including Wnt/β-catenin, Prolactin, and insulin-like growth factor (IGF)1 signaling. Leiomyomas with HMGA2 aberrations displayed highly significant up-regulation of the proto-oncogene pleomorphic adenoma gene 1 (PLAG1), suggesting that HMGA2 promotes tumorigenesis through PLAG1 activation. This was supported by the identification of genetic PLAG1 alterations resulting in expression signatures as seen in leiomyomas with HMGA2 aberrations. RAD51 paralog B (RAD51B), the preferential translocation partner of HMGA2, was up-regulated in MED12 mutant lesions, suggesting a role for this gene in the genesis of leiomyomas. FH-deficient leiomyomas were uniquely characterized by activation of nuclear factor erythroid 2-related factor 2 (NRF2) target genes, supporting the hypothesis that accumulation of fumarate leads to activation of the oncogenic transcription factor NRF2. This study emphasizes the need for molecular stratification in leiomyoma research and possibly in clinical practice as well. Further research is needed to determine whether the candidate biomarkers presented herein can provide guidance for managing the millions of patients affected by these lesions.

TET2Overexpression in Chronic Lymphocytic Leukemia Is Unrelated to the Presence ofTET2Variations

TET2is involved in a variety of hematopoietic malignancies, mainly in myeloid malignancies. Most mutations ofTET2have been identified in myeloid disorders, but some have also recently been described in mature lymphoid neoplasms. In contrast to the large amount of data about mutations ofTET2, some data are available for gene expression. Moreover, the role of TET2 in chronic lymphocytic leukemia (CLL) is unknown. This study analyzes bothTET2expression and mutations in 48 CLL patients.TET2expression was analyzed by exon arrays and quantitative real-time polymerase chain reaction (qRT-PCR). Next-generation sequencing (NGS) technology was applied to investigate the presence ofTET2variations. Overexpression ofTET2was observed in B-cell lymphocytes from CLL patients compared with healthy donors (P= 0.004). In addition, in CLL patients, an overexpression ofTET2was also observed in the clonal B cells compared with the nontumoral cells (P= 0.002). However, no novel mutations were observed. Therefore, overexpression ofTET2in CLL seems to be unrelated to the presence of genomicTET2variations.