A Transcriptional Landscape Underlying Sugar Import for Grain Set in Maize

2022 ◽  
Author(s):  
Si Shen ◽  
Si Ma ◽  
Xian‐Min Chen ◽  
Fei Yi ◽  
Bin‐Bin Li ◽  
...  
BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Eddie Luidy Imada ◽  
Diego Fernando Sanchez ◽  
Wikum Dinalankara ◽  
Thiago Vidotto ◽  
Ericka M. Ebot ◽  
...  

Abstract Background PTEN is the most frequently lost tumor suppressor in primary prostate cancer (PCa) and its loss is associated with aggressive disease. However, the transcriptional changes associated with PTEN loss in PCa have not been described in detail. In this study, we highlight the transcriptional changes associated with PTEN loss in PCa. Methods Using a meta-analysis approach, we leveraged two large PCa cohorts with experimentally validated PTEN and ERG status by Immunohistochemistry (IHC), to derive a transcriptomic signature of PTEN loss, while also accounting for potential confounders due to ERG rearrangements. This signature was expanded to lncRNAs using the TCGA quantifications from the FC-R2 expression atlas. Results The signatures indicate a strong activation of both innate and adaptive immune systems upon PTEN loss, as well as an expected activation of cell-cycle genes. Moreover, we made use of our recently developed FC-R2 expression atlas to expand this signature to include many non-coding RNAs recently annotated by the FANTOM consortium. Highlighting potential novel lncRNAs associated with PTEN loss and PCa progression. Conclusion We created a PCa specific signature of the transcriptional landscape of PTEN loss that comprises both the coding and an extensive non-coding counterpart, highlighting potential new players in PCa progression. We also show that contrary to what is observed in other cancers, PTEN loss in PCa leads to increased activation of the immune system. These findings can help the development of new biomarkers and help guide therapy choices.


2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Robin-Lee Troskie ◽  
Yohaann Jafrani ◽  
Tim R. Mercer ◽  
Adam D. Ewing ◽  
Geoffrey J. Faulkner ◽  
...  

AbstractPseudogenes are gene copies presumed to mainly be functionless relics of evolution due to acquired deleterious mutations or transcriptional silencing. Using deep full-length PacBio cDNA sequencing of normal human tissues and cancer cell lines, we identify here hundreds of novel transcribed pseudogenes expressed in tissue-specific patterns. Some pseudogene transcripts have intact open reading frames and are translated in cultured cells, representing unannotated protein-coding genes. To assess the biological impact of noncoding pseudogenes, we CRISPR-Cas9 delete the nucleus-enriched pseudogene PDCL3P4 and observe hundreds of perturbed genes. This study highlights pseudogenes as a complex and dynamic component of the human transcriptional landscape.


2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A646-A647
Author(s):  
Max Meneveau ◽  
Pankaj Kumar ◽  
Kevin Lynch ◽  
Karlyn Pollack ◽  
Craig Slingluff

BackgroundVaccines are a promising therapeutic for patients with advanced cancer, but achieving robust T-cell responses remains a challenge. Melanoma-associated antigen-A3 (MAGE-A3) in combination with adjuvant AS15 (a formulation of Toll-Like-Receptor (TLR)-4 and 9 agonists and a saponin), induced systemic CD4+ T-cell responses in 50% of patients when given subcutaneously/intradermally. Little is known about the transcriptional landscape of the vaccine-site microenvironment (VSME) of patients with systemic T-cell responses versus those without. We hypothesized that patients with systemic T-cell responses to vaccination would exhibit increased immune activation in the VSME, higher dendritic cell (DC) activation/maturation, TLR-pathway activation, and enhanced Th1 signatures.MethodsBiopsies of the VSME were obtained from participants on the Mel55 clinical trial (NCT01425749) who were immunized with MAGE-A3/AS15. Biopsies were taken 8 days after immunization. T-cell response to MAGE-A3 was assessed in PBMC after in-vitro stimulation with recMAGE-A3, by IFNγ ELISPOT assay. Gene expression was assessed by RNAseq using DESeq2. Comparisons were made between immune-responders (IR), non-responders (NR), and normal skin controls. FDR p<0.01 was considered significant.ResultsFour IR, four NR, and three controls were evaluated. The 500 most variable genes were used for principal component analysis (PCA). Two IR samples were identified as outliers on PCA and excluded from further analysis. There were 882 differentially expressed genes (DEGs) in the IR group vs the NR group (figure 1A). Unsupervised clustering of the top 500 DEGs revealed clustering according to the experimental groups (figure 1B). Of the 10 most highly upregulated DEGs, 9 were immune-related (figure 1C). Gene-set enrichment analysis revealed that immune-related pathways were highly enriched in IRs vs NRs (figure 1D). CD4 and CD8 expression did not differ between IR and NR (figure 2A), though both were higher in IR compared to control. Markers of DC activation/maturation were higher in IR vs NR (figure 2B), as were several Th1 associated genes (figure 2C). Interestingly, markers of exhaustion were higher in IR v NR (figure 2D). Expression of numerous TLR-pathway genes was higher in IR vs NR, including MYD88, but not TICAM1 (figure 2E).Abstract 611 Figure 1Gene expression profiling of vaccine site samples from patients immunized with MAGE-A3/AS15. (A) Volcano plots showing the distribution of differentially expressed genes (DEGs) between immune responders (IR) and non-responders (NR), IR and control, and NR and control. (B) Heatmap of the top 500 most differentially expressed genes demonstrating hierarchical clustering of sequenced samples according to IR, NR, and control. (C) Table showing the 10 most highly up and down-regulated genes in IR compared to NR. 9 of the top 10 most highly up-regulated genes are related to the immune response. (D) Enrichment plots from a gene set enrichment analysis highlighting the upregulation of immune related pathways in IR compared to NR. Gene set enrichment data was generated from the Reactome gene set database and included all expressed genes. Significance was set at FDR p <0.01Abstract 611 Figure 2Expression of T-cell markers in IR vs NR vs Control samples in the vaccine site microenvironment (VSME). (A) T-cell markers showing similar expression in IR vs NR but higher expression in IR vs control. (B) Markers of dendritic cell activation and maturation in the VSME which are higher in IR vs control but not IR vs NR. (B) Transcription factors and genes associated with Th1/Th2 responses within the VSME. (D) Genes associated with T-cell exhaustion at the VSME. (E) Expression of TLR pathway genes in the VSME. Expression data is provided in terms of normalized counts. Bars demonstrate median and interquartile range. N=9. IR = immune responder, NR = non-responder, TLR = Toll-like Receptor. * = <0.01, ** < 0.001, *** <0.0001, **** < 0.00001ConclusionsThese findings suggest a unique immune-transcriptional landscape in the VSME is associated with circulating T-cell responses to immunization, with differences in DC activation/maturation, Th1 response, and TLR signaling. Thus, immunologic changes in the VSME are useful predictors of systemic immune response, and host factors that modulate immune-related signaling at the vaccine site may have concordant systemic effects on promoting or limiting immune responses to vaccines.Trial RegistrationSamples for this work were collected from patients enrolled on the Mel55 clinical trial NCT01425749.Ethics ApprovalThis work was completed after approval from the UVA institutional review board IRB-HSR# 15398.


2021 ◽  
Vol 22 (14) ◽  
pp. 7340
Author(s):  
Alvina I. Khamidullina ◽  
Ekaterina A. Varlamova ◽  
Nour Alhuda Hammoud ◽  
Margarita A. Yastrebova ◽  
Alexandra V. Bruter

Blood malignancies often arise from undifferentiated hematopoietic stem cells or partially differentiated stem-like cells. A tight balance of multipotency and differentiation, cell division, and quiescence underlying normal hematopoiesis requires a special program governed by the transcriptional machinery. Acquisition of drug resistance by tumor cells also involves reprogramming of their transcriptional landscape. Limiting tumor cell plasticity by disabling reprogramming of the gene transcription is a promising strategy for improvement of treatment outcomes. Herein, we review the molecular mechanisms of action of transcription-targeted drugs in hematological malignancies (largely in leukemia) with particular respect to the results of clinical trials.


Animals ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 1443
Author(s):  
Susana A. Teixeira ◽  
Daniele B. D. Marques ◽  
Thaís C. Costa ◽  
Haniel C. Oliveira ◽  
Karine A. Costa ◽  
...  

Since pre- and postnatal development are programmed during early prenatal life, studies addressing the complete transcriptional landscape during organogenesis are needed. Therefore, we aimed to disentangle differentially expressed (DE) genes between fetuses (at 35 days old) and embryos (at 25 days old) through RNA-sequencing analysis using the pig as model. In total, 1705 genes were DE, including the top DE IBSP, COL6A6, HBE1, HBZ, HBB, and NEUROD6 genes, which are associated with developmental transition from embryos to fetuses, such as ossification, skeletal muscle development, extracellular matrix organization, cardiovascular system, erythrocyte differentiation, and neuronal system. In pathway analysis, embryonic development highlighted those mainly related to morphogenic signaling and cell interactions, which are crucial for transcriptional control during the establishment of the main organs in early prenatal development, while pathways related to myogenesis, neuronal development, and cardiac and striated muscle contraction were enriched for fetal development, according to the greater complexity of organs and body structures at this developmental stage. Our findings provide an exploratory and informative transcriptional landscape of pig organogenesis, which might contribute to further studies addressing specific developmental events in pigs and in other mammals.


2013 ◽  
Vol 6 (6) ◽  
pp. 1988-1991 ◽  
Author(s):  
Subramanian Sankaranarayanan ◽  
Muhammad Jamshed ◽  
Srijani Deb ◽  
Kate Chatfield-Reed ◽  
Eun-Joo Gina Kwon ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document