1,721,040 research outputs found
Predicting gene expression in the human malaria parasite <i>Plasmodium falciparum</i> using histone modification, nucleosome positioning, and 3D localization features
Full text linkEmpirical evidence suggests that the malaria parasite Plasmodium falciparum employs a broad range of mechanisms to regulate gene transcription throughout the organism’s complex life cycle. To better understand this regulatory machinery, we assembled a rich collection of genomic and epigenomic data sets, including information about transcription factor (TF) binding motifs, patterns of covalent histone modifications, nucleosome occupancy, GC content, and global 3D genome architecture. We used these data to train machine learning models to discriminate between high-expression and low-expression genes, focusing on three distinct stages of the red blood cell phase of the Plasmodium life cycle. Our results highlight the importance of histone modifications and 3D chromatin architecture in Plasmodium transcriptional regulation and suggest that AP2 transcription factors may play a limited regulatory role, perhaps operating in conjunction with epigenetic factors.</div
Homotopies: A Panacea or Just Another Method?
No full textA general framework is presented for the solving of non-linear equations. Also, a discussion about its potential applications in the field of computer vision is made and illustrated by an example that shows how one can relate the solutions to the shape-from-shading problem through scale space. The methods presented seem to have been known since the 19th century; however, it was not until 1953 that the first practical applications of the relevant idea appeared
Short RNAs: How Big Is This Iceberg?
No full textSummaryRecent studies have reported the identification of piwi-associated RNAs (piRNAs) in Drosophila somatic cells. Interestingly, these piRNAs derive from the 3′ untranslated regions of a subset of transcribed protein-coding genes and, experimentation suggests, might control the expression of other protein-coding transcripts. Studies of additional organisms support the new pathway's presence across animals
Session #4: Short Regulatory RNAs and their Impact Depend on Personal Attributes: Implications for Identifying Novel Biomarkers and Novel Therapeutic Targets, and for Precision Medicine
No full textWe have been studying three types of short regulatory RNAs. They include: the isoforms of microRNAs that are known as “isomiRs”; the short RNA fragments that are derived from nuclear and mitochondrial transfer RNAs and are known as “tRFs”; and, the short RNA fragments that are derived from nuclear and mitochondrial ribosomal RNAs and are known as “rRFs.” By analyzing datasets from thousands of healthy individuals and patients, we were able to show that isomiRs, tRFs and rRFs are produced in a regimented manner and are not degradation products. We also showed that the identities and abundances of all three RNA types depend on personal attributes such as sex, population-of-origin, and race/ethnicity, as well as on tissue, tissue state, and disease. Moreover, parallel work by others and us showed that isomiRs, tRFs and rRFs regulate messenger RNA and protein abundance. Taken together, the findings strongly suggest that, in health and in disease, the abundance of proteins in a given tissue depends on a person’s sex, population-of-origin and race/ethnicity. In fact, the available data indicates that all three categories of molecules are implicated in mechanistic events that contribute to disparities by race/ethnicity or by sex. So far, we have provided evidence to this effect for a number of diseases with documented disparities including triple negative breast cancer, prostate cancer, lung cancer, bladder cancer, and kidney cancer.
In this presentation, I will provide an overview of our work with these molecules. I will also discuss how isomiRs, tRFs and rRFs can serve as powerful biomarkers for diagnosis and prognosis, and as novel candidate therapeutic targets. Lastly, I will describe the implications of these findings for the study of the molecular underpinnings of health disparities and for Precision Medicine
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
MiR-103a-3p targets the 5\u27 UTR of GPRC5A in pancreatic cells.
Full text linkMicroRNAs (miRNAs) are short noncoding RNAs that regulate the expression of their targets in a sequence-dependent manner. For protein-coding transcripts, miRNAs regulate expression levels through binding sites in either the 3\u27 untranslated region (3\u27 UTR) or the amino acid coding sequence (CDS) of the targeted messenger RNA (mRNA). Currently, for the 5\u27 untranslated region (5\u27 UTR) of mRNAs, very few naturally occurring examples exist whereby the targeting miRNA down-regulates the expression of the corresponding mRNA in a seed-dependent manner. Here we describe and characterize two miR-103a-3p target sites in the 5\u27 UTR of GPRC5A, a gene that acts as a tumor suppressor in some cancer contexts and as an ongocene in other cancer contexts. In particular, we show that the interaction of miR-103a-3p with each of these two 5\u27 UTR targets reduces the expression levels of both GPRC5A mRNA and GPRC5A protein in one normal epithelial and two pancreatic cancer cell lines. By ectopically expressing sponges that contain instances of the wild-type 5\u27 UTR targets we also show that we can reduce miR-103a-3p levels and increase GPRC5A mRNA and protein levels. These findings provide some first knowledge on the post-transcriptional regulation of this tumor suppressor/oncogene and present additional evidence for the participation of 5\u27 UTRs in miRNA driven post-transcriptional regulatory control
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