Previous studies employing a 79-nucleotide (nt) RNA indicated that this RNA could form two bands in a native polyacrylamide gel while one band was observed in a denaturing gel. This report describes an investigation on the nature of the two corresponding structures and the segment responsible for forming the slower mobility band. Sedimentation equilibrium of the 79-nt RNA was consistent with the two gel bands corresponding to monomer and dimer forms. The portion of the RNA required for dimer formation was explored using a secondary structure prediction algorithm of two 79-nt RNAs linked in a head-to-tail fashion. The predicted structure suggested that the first 21-nt at the 5' end of each RNA formed a self-complementary duplex. A ribonuclease H assay carried out with RNA prepared as monomer (M), or a mixture of monomer and dimer (M/D), gave results consistent with the predicted M and D structures. Gel mobility experiments on 5' and 3' segments of the 79-nt RNA also indicated that dimer formation was due to the 21-nt 5' end. Studies on the 21-nt RNA molecule and sequence variants showed that this sequence can form a hairpin and a dimer complex. Unexpectedly, the hairpin to dimer conversion was shown to occur at high efficiency in frozen solution, although little or no conversion was observed above 0 degrees C. The results indicate that a freezing environment can promote formation of intermolecular RNA complexes from stable RNA hairpins, supporting the notion that this environment could have played a role in the evolution of RNA complexity.
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http://dx.doi.org/10.1261/rna.433307 | DOI Listing |
Clin Cancer Res
January 2025
ACTREC, Tata Memorial Centre, Navi Mumbai, Maharashtra, India.
Purpose: Identifying therapeutic targets for Signet Ring Cell Carcinoma (SRCC) of the colon and rectum is a clinical challenge due to the lack of Patient-Derived Organoids (PDO) or Xenografts (PDX). We present a robust method to establish PDO and PDX models to answer address this unmet need. We demonstrate that these models identify novel therapeutic strategies targeting therapy resistance and peritoneal metastasis.
View Article and Find Full Text PDFBrief Bioinform
November 2024
Center for Artificial Intelligence Research, Wake Forest University School of Medicine, Winston-Salem, NC 27101, United States.
Pathway analysis plays a critical role in bioinformatics, enabling researchers to identify biological pathways associated with various conditions by analyzing gene expression data. However, the rise of large, multi-center datasets has highlighted limitations in traditional methods like Over-Representation Analysis (ORA) and Functional Class Scoring (FCS), which struggle with low signal-to-noise ratios (SNR) and large sample sizes. To tackle these challenges, we use a deep learning-based classification method, Gene PointNet, and a novel $P$-value computation approach leveraging the confusion matrix to address pathway analysis tasks.
View Article and Find Full Text PDFBrief Bioinform
November 2024
Department of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.
This study aimed to investigate the genetic association between glioblastoma (GBM) and unsupervised deep learning-derived imaging phenotypes (UDIPs). We employed a combination of genome-wide association study (GWAS) data, single-nucleus RNA sequencing (snRNA-seq), and scPagwas (pathway-based polygenic regression framework) methods to explore the genetic links between UDIPs and GBM. Two-sample Mendelian randomization analyses were conducted to identify causal relationships between UDIPs and GBM.
View Article and Find Full Text PDFSTAR Protoc
January 2025
Department of Statistics, University of Georgia, 310 Herty Drive, Athens, GA 30602, USA. Electronic address:
Spatial transcriptomics enhances our understanding of cellular organization by mapping gene expression data to precise tissue locations. Here, we present a protocol for using weighted ensemble method for spatial transcriptomics (WEST), which uses ensemble techniques to boost the robustness and accuracy of existing algorithms. We describe steps for preprocessing data, obtaining embeddings from individual algorithms, and ensemble integrating all embeddings as a similarity matrix.
View Article and Find Full Text PDFSci Transl Med
January 2025
Division of Pediatric Hematology/Oncology, Boston Children's Hospital, Boston, MA 02115, USA.
Tissue-specific T cell immune responses play a critical role in maintaining organ health but can also drive immune pathology during both autoimmunity and alloimmunity. The mechanisms controlling intratissue T cell programming remain unclear. Here, we leveraged a nonhuman primate model of acute graft-versus-host disease (aGVHD) after allogeneic hematopoietic stem cell transplantation to probe the biological underpinnings of tissue-specific alloimmune disease using a comprehensive systems immunology approach including multiparameter flow cytometry, population-based transcriptional profiling, and multiplexed single-cell RNA sequencing and TCR sequencing.
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