Identification of LncRNAs as Therapeutic Targets in Chronic Lymphocytic Leukemia

Chronic Lymphocytic Leukemia (CLL) is one kind of blood cancer that has a very heterogeneous biological background, which results in diverse stages of the CLL and complex treatment strategies. However, a small part of the tumor may disappear without receiving any treatment. This condition is known as “spontaneous regression” and occurs as a result of a poorly investigated mechanism. Exposing the underlying causes of this condition can lead to a novel treatment approach for CLL and other types of cancer. While most such mechanisms have been assumed to be directly linked to protein coding genes, a recent approach was aimed to carry out more comprehensive studies by focusing on non-protein coding genes as well as protein-coding genes at the RNA level. In this article, we applied in-silico analysis of total RNA expression data from 24 CLL samples to determine possible regulatory mechanisms of spontaneous regression in CLL. These were selected by comparing spontaneous regression with progressive samples of CLL at the transcriptional level. As a result, 33 lncRNAs were found to be significantly differentially expressed among these conditions based on differential gene expression analysis. Current study suggested lncRNAs, PTPN22-AS1, PCF11-AS1, SYNGAP1-AS1, PRRT3-AS1 and H1FX-AS1 as potential therapeutic targets to trigger spontaneous regression. Eventually, the results presented here reveal new insights into the spontaneous regression and the relation with the non-coding RNAs, particularly lncRNAs

Learning to Solve Voxel Building Embodied Tasks from Pixels and Natural Language Instructions

The adoption of pre-trained language models to generate action plans for embodied agents is a promising research strategy. However, execution of instructions in real or simulated environments requires verification of the feasibility of actions as well as their relevance to the completion of a goal. We propose a new method that combines a language model and reinforcement learning for the task of building objects in a Minecraft-like environment according to the natural language instructions. Our method first generates a set of consistently achievable sub-goals from the instructions and then completes associated sub-tasks with a pre-trained RL policy. The proposed method formed the RL baseline at the IGLU 2022 competition.Comment: 6 pages, 3 figure

The human RNA polymerase I structure reveals an HMG-like docking domain specific to metazoans

Transcription of the ribosomal RNA precursor by RNA polymerase (Pol) I is a major determinant of cellular growth, and dysregulation is observed in many cancer types. Here, we present the purification of human Pol I from cells carrying a genomic GFP fusion on the largest subunit allowing the structural and functional analysis of the enzyme across species. In contrast to yeast, human Pol I carries a single-subunit stalk, and in vitro transcription indicates a reduced proofreading activity. Determination of the human Pol I cryo-EM reconstruction in a close-to-native state rationalizes the effects of disease-associated mutations and uncovers an additional domain that is built into the sequence of Pol I subunit RPA1. This “dock II” domain resembles a truncated HMG box incapable of DNA binding which may serve as a downstream transcription factor–binding platform in metazoans. Biochemical analysis, in situ modelling, and ChIP data indicate that Topoisomerase 2a can be recruited to Pol I via the domain and cooperates with the HMG box domain–containing factor UBF. These adaptations of the metazoan Pol I transcription system may allow efficient release of positive DNA supercoils accumulating downstream of the transcription bubble

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world\u27s major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (−0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km² resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e., offset) between in-situ soil temperature measurements, based on time series from over 1200 1-km² pixels (summarized from 8500 unique temperature sensors) across all the world’s major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in-situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Global maps of soil temperature.

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0-5 and 5-15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

An Association Study of DNA Methylation and Gene Expression in Angelman Syndrome: A Bioinformatics Approach

Angelman syndrome (AS) is a neurodevelopmental disorder caused by the loss of function of the E3-ligase UBE3A. Despite multiple studies, AS pathophysiology is still obscure and has mostly been explored in rodent models of the disease. In recent years, a growing body of studies has utilized omics datasets in the attempt to focus research regarding the pathophysiology of AS. Here, for the first time, we utilized a multi-omics approach at the epigenomic level and the transcriptome level, for human-derived neurons. Using publicly available datasets for DNA methylation and gene expression, we found genome regions in proximity to gene promoters and intersecting with gene-body regions that were differentially methylated and differentially expressed in AS. We found that overall, the genome in AS postmortem brain tissue was hypo-methylated compared to healthy controls. We also found more upregulated genes than downregulated genes in AS. Many of these dysregulated genes in neurons obtained from AS patients are known to be critical for neuronal development and synaptic functioning. Taken together, our results suggest a list of dysregulated genes that may be involved in AS development and its pathological features. Moreover, these genes might also have a role in neurodevelopmental disorders similar to AS

Novel Insights into the Role of UBE3A in Regulating Apoptosis and Proliferation

The UBE3A gene codes for a protein with two known functions, a ubiquitin E3-ligase which catalyzes ubiquitin binding to substrate proteins and a steroid hormone receptor coactivator. UBE3A is most famous for its critical role in neuronal functioning. Lack of UBE3A protein expression leads to Angelman syndrome (AS), while its overexpression is associated with autism. In spite of extensive research, our understanding of UBE3A roles is still limited. We investigated the cellular and molecular effects of Ube3a deletion in mouse embryonic fibroblasts (MEFs) and Angelman syndrome (AS) mouse model hippocampi. Cell cultures of MEFs exhibited enhanced proliferation together with reduced apoptosis when Ube3a was deleted. These findings were supported by transcriptome and proteome analyses. Furthermore, transcriptome analyses revealed alterations in mitochondria-related genes. Moreover, an analysis of adult AS model mice hippocampi also found alterations in the expression of apoptosis- and proliferation-associated genes. Our findings emphasize the role UBE3A plays in regulating proliferation and apoptosis and sheds light into the possible effects UBE3A has on mitochondrial involvement in governing this balance