Exploring Regulatory Roles of Transposable Elements in EMT and MET through Data-Driven Analysis: Insights from regulaTER.

Gene expression is regulated at the transcriptional and translational levels and a plethora of epigenetic mechanisms. Regulation of gene expression by transposable elements is well documented. However, a comprehensive analysis of their regulatory roles is challenging due to the lack of dedicated approaches to define their contribution.

Physicochemical differences between camelid single-domain antibodies and mammalian antibodies.

Background/aim: In recent years, single-domain antibodies, also known as nanobodies, have emerged as an alternative to full immunoglobulin Gs (IgGs), due to their various advantages, including increased solubility, faster clearance, and cheaper production. Nanobodies are generally derived from the variable domain of the camelid heavy-chain-only immunoglobulin Gs (hcIgGs). Due to the high sequence homology between variable heavy chains of camelids (VHs) and humans (Vs), hcIgGs are ideal candidates for nanobody development.

PlanTEnrichment: A How-to Guide on Rapid Identification of Transposable Elements Associated with Regions of Interest in Select Plant Genomes.

Transposable elements (TEs) are repeat elements that can relocate or create novel copies of themselves in the genome and contribute to genomic complexity and expansion, via events such as chromosome recombination or regulation of gene expression. However, given the large number of such repeats across the genome, identifying repeats of interest can be a challenge in even well-annotated genomes, especially in more complex, TE-rich plant genomes. Here, we describe a protocol for PlanTEnrichment, a database we created comprising information on 11 plant genomes to analyze stress-associated TEs using publicly available data.

Transcriptome Dynamics of Human Neuronal Differentiation From iPSC.

The generation and use of induced pluripotent stem cells (iPSCs) in order to obtain all differentiated adult cell morphologies without requiring embryonic stem cells is one of the most important discoveries in molecular biology. Among the uses of iPSCs is the generation of neuron cells and organoids to study the biological cues underlying neuronal and brain development, in addition to neurological diseases. These iPSC-derived neuronal differentiation models allow us to examine the gene regulatory factors involved in such processes.

In Silico Identification of Stress-Associated Transposable Elements in Arabidopsis thaliana Using Public Transcriptome Data.

Transposable elements (TEs) have been associated with stress response in many plants, making them a key target of study. However, the high variability, genomic repeat-heavy nature, and widely noncoding character of TEs have made them difficult to study using non-specialized methods, whether experimental or computational. In this chapter, we introduce two computational workflows to analyze transposable elements using publicly available transcriptome data.

Different selection dynamics of S and RdRp between SARS-CoV-2 genomes with and without the dominant mutations.

SARS-CoV-2 is a betacoronavirus responsible for the COVID-19 pandemic that has affected millions of people worldwide. Pharmaceutical research against COVID-19 and the most frequently used tests for SARS-CoV-2 both depend on the genomic and peptide sequences of the virus for their robustness. Therefore, understanding the mutation rates and content of the virus is critical.

Current mutatome of SARS-CoV-2 in Turkey reveals mutations of interest.

As the underlying pathogen for the COVID-19 pandemic that has affected tens of millions of lives worldwide, SARS-CoV-2 and its mutations are among the most urgent research topics worldwide. Mutations in the virus genome can complicate attempts at accurate testing or developing a working treatment for the disease. Furthermore, because the virus uses its own proteins to replicate its genome, rather than host proteins, mutations in the replication proteins can have cascading effects on the mutation load of the virus genome.

Mutations of SARS-CoV-2 nsp14 exhibit strong association with increased genome-wide mutation load.

SARS-CoV-2 is a betacoronavirus responsible for COVID-19, a pandemic with global impact that first emerged in late 2019. Since then, the viral genome has shown considerable variance as the disease spread across the world, in part due to the zoonotic origins of the virus and the human host adaptation process. As a virus with an RNA genome that codes for its own genomic replication proteins, mutations in these proteins can significantly impact the variance rate of the genome, affecting both the survival and infection rate of the virus, and attempts at combating the disease.

Mutation density changes in SARS-CoV-2 are related to the pandemic stage but to a lesser extent in the dominant strain with mutations in spike and RdRp.

Since its emergence in Wuhan, China in late 2019, the origin and evolution of SARS-CoV-2 have been among the most debated issues related to COVID-19. Throughout its spread around the world, the viral genome continued acquiring new mutations and some of them became widespread. Among them, 14408 C>T and 23403 A>G mutations in RdRp and S, respectively, became dominant in Europe and the US, which led to debates regarding their effects on the mutability and transmissibility of the virus.

RdRp mutations are associated with SARS-CoV-2 genome evolution.

COVID-19, caused by the novel SARS-CoV-2 virus, started in China in late 2019, and soon became a global pandemic. With the help of thousands of viral genome sequences that have been accumulating, it has become possible to track the evolution of the viral genome over time as it spread across the world. An important question that still needs to be answered is whether any of the common mutations affect the viral properties, and therefore the disease characteristics.

Genes associated with T helper 17 cell differentiation and function.

Interleukin-17 (IL-17)-producing T helper cells (Th17 cells) constitute a lineage of CD4 effector T helper cells that is distinct from the Th1 and Th2 CD4 phenotypes. In humans, Th17 differentiation is induced in the presence of the cytokines IL-1 beta, IL-6 and TGF beta, whereas IL-23 maintains Th17 survival. Effector human Th17 cells express several cytokines and cell surface markers, including IL-17A, IL-17F, IL-22, IL-26, CCR6 and TNFalpha.