More Like this

1. In silico model for miRNA-mediated regulatory network in cancer

   https://doi.org/10.1093/bib/bbab264  

   Ahmed, Khandakar Tanvir; Sun, Jiao; Chen, William; Martinez, Irene; Cheng, Sze; Zhang, Wencai; Yong, Jeongsik; Zhang, Wei (January 2021, Briefings in Bioinformatics)

   null (Ed.)

   Deregulation of gene expression is associated with the pathogenesis of numerous human diseases including cancer. Current data analyses on gene expression are mostly focused on differential gene/transcript expression in big data-driven studies. However, a poor connection to the proteome changes is a widespread problem in current data analyses. This is partly due to the complexity of gene regulatory pathways at the post-transcriptional level. In this study, we overcome these limitations and introduce a graph-based learning model, PTNet, which simulates the microRNAs (miRNAs) that regulate gene expression post-transcriptionally in silico. Our model does not require large-scale proteomics studies to measure the protein expression and can successfully predict the protein levels by considering the miRNA–mRNA interaction network, the mRNA expression, and the miRNA expression. Large-scale experiments on simulations and real cancer high-throughput datasets using PTNet validated that (i) the miRNA-mediated interaction network affects the abundance of corresponding proteins and (ii) the predicted protein expression has a higher correlation with the proteomics data (ground-truth) than the mRNA expression data. The classification performance also shows that the predicted protein expression has an improved prediction power on cancer outcomes compared to the prediction done by the mRNA expression data only or considering both mRNA and miRNA. Availability: PTNet toolbox is available at http://github.com/CompbioLabUCF/PTNet 

   more » « less
2. An ancient and essential miRNA family controls cellular interaction pathways in C. elegans

   https://doi.org/10.1126/sciadv.adz1934  

   Santillan, Emilio M; Cormack, Eric D; Wang, Jingkui; Rodriguez-Steube, Micaela; Cochella, Luisa (September 2025, Science Advances)

   The transition from unicellular to multicellular life required the acquisition of coordinated and regulated cellular behaviors, including adhesion and migration. In metazoans, this involves adhesion proteins, signaling systems, and an elaborate extracellular matrix (ECM) that contributes to adhesion and signaling interactions. Innovations that enabled complex multicellularity occurred through new genes in these pathways, novel functions for existing genes, and regulatory changes. Gene regulation by microRNAs (miRNAs) expanded with multicellularity. A single miRNA, miR-100, arose in the last common eumetazoan ancestor and is widely conserved across animals. We reveal the molecular function of itsC. eleganshomolog, the miR-51 family. This family acts in a dose-dependent manner to control morphogenesis by regulating several genes involved in cell signaling, adhesion, and migration, including ECM modifiers—specifically heparan sulfate sulfotransferases (HSTs). Some of these targets are also predicted to be conserved targets across vertebrates. Our work suggests that this miRNA provided an innovation in the regulation of cellular interactions early in metazoan evolution. 

   more » « less
3. A mixed antagonistic/synergistic miRNA repression model enables accurate predictions of multi-input miRNA sensor activity

   https://doi.org/10.1038/s41467-018-04575-0  

   Gam, Jeremy J.; Babb, Jonathan; Weiss, Ron (December 2018, Nature Communications)
4. Anti-miRNA Oligonucleotide Therapy for Chondrosarcoma

   https://doi.org/10.1158/1535-7163.MCT-18-1020  

   Sun, X; Chen, Y; Yu, H; Machan, J T; Alladin, A; Ramirez, J; Taliano, R; Hart, J; Chen, Q; Terek, R M. (January 2019, Molecular cancer therapeutics)
5. Computational annotation of miRNA transcription start sites

   https://doi.org/10.1093/bib/bbz178  

   Wang, Saidi; Talukder, Amlan; Cha, Mingyu; Li, Xiaoman; Hu, Haiyan (January 2020, Briefings in Bioinformatics)

   Abstract Motivation MicroRNAs (miRNAs) are small noncoding RNAs that play important roles in gene regulation and phenotype development. The identification of miRNA transcription start sites (TSSs) is critical to understand the functional roles of miRNA genes and their transcriptional regulation. Unlike protein-coding genes, miRNA TSSs are not directly detectable from conventional RNA-Seq experiments due to miRNA-specific process of biogenesis. In the past decade, large-scale genome-wide TSS-Seq and transcription activation marker profiling data have become available, based on which, many computational methods have been developed. These methods have greatly advanced genome-wide miRNA TSS annotation. Results In this study, we summarized recent computational methods and their results on miRNA TSS annotation. We collected and performed a comparative analysis of miRNA TSS annotations from 14 representative studies. We further compiled a robust set of miRNA TSSs (RSmirT) that are supported by multiple studies. Integrative genomic and epigenomic data analysis on RSmirT revealed the genomic and epigenomic features of miRNA TSSs as well as their relations to protein-coding and long non-coding genes. Contact xiaoman@mail.ucf.edu, haihu@cs.ucf.edu 

   more » « less