Mapping Posttranscriptional Regulation of the Human Glycome Uncovers microRNA Defining the Glycocode

Cell surface glycans form a critical interface with the biological milieu, informing diverse processes from the inflammatory cascade to cellular migration. Assembly of discrete carbohydrate structures requires the coordinated activity of a repertoire of proteins, including glycosyltransferases and glycosidases. Little is known about the regulatory networks controlling this complex biosynthetic process. Recent work points to a role for microRNA (miRNA) in the regulation of specific glycan biosynthetic enzymes. Herein we take a unique systems-based approach to identify connections between miRNA and the glycome. By using our glycomic analysis platform, lectin microarrays, we identify glycosylation signatures in the NCI-60 cell panel that point to the glycome as a direct output of genomic information flow. Integrating our glycomic dataset with miRNA data, we map miRNA regulators onto genes in glycan biosynthetic pathways (glycogenes) that generate the observed glycan structures. We validate three of these predicted miRNA/glycogene regulatory networks: high mannose, fucose, and terminal β-GalNAc, identifying miRNA regulation that would not have been observed by traditional bioinformatic methods. Overall, our work reveals critical nodes in the global glycosylation network accessible to miRNA regulation, providing a bridge between miRNA-mediated control of cell phenotype and the glycome

Mapping and functional characterization of structural variation in 1060 pig genomes

BACKGROUND: Structural variations (SVs) have significant impacts on complex phenotypes by rearranging large amounts of DNA sequence.RESULTS: We present a comprehensive SV catalog based on the whole-genome sequence of 1060 pigs (Sus scrofa) representing 101 breeds, covering 9.6% of the pig genome. This catalog includes 42,487 deletions, 37,913 mobile element insertions, 3308 duplications, 1664 inversions, and 45,184 break ends. Estimates of breed ancestry and hybridization using genotyped SVs align well with those from single nucleotide polymorphisms. Geographically stratified deletions are observed, along with known duplications of the KIT gene, responsible for white coat color in European pigs. Additionally, we identify a recent SINE element insertion in MYO5A transcripts of European pigs, potentially influencing alternative splicing patterns and coat color alterations. Furthermore, a Yorkshire-specific copy number gain within ABCG2 is found, impacting chromatin interactions and gene expression across multiple tissues over a stretch of genomic region of ~200 kb. Preliminary investigations into SV's impact on gene expression and traits using the Pig Genotype-Tissue Expression (PigGTEx) data reveal SV associations with regulatory variants and gene-trait pairs. For instance, a 51-bp deletion is linked to the lead eQTL of the lipid metabolism regulating gene FADS3, whose expression in embryo may affect loin muscle area, as revealed by our transcriptome-wide association studies.CONCLUSIONS: This SV catalog serves as a valuable resource for studying diversity, evolutionary history, and functional shaping of the pig genome by processes like domestication, trait-based breeding, and adaptive evolution.</p

A compendium of genetic regulatory effects across pig tissues

The Farm Animal Genotype-Tissue Expression (FarmGTEx) project has been established to develop a public resource of genetic regulatory variants in livestock, which is essential for linking genetic polymorphisms to variation in phenotypes, helping fundamental biological discovery and exploitation in animal breeding and human biomedicine. Here we show results from the pilot phase of PigGTEx by processing 5,457 RNA-sequencing and 1,602 whole-genome sequencing samples passing quality control from pigs. We build a pig genotype imputation panel and associate millions of genetic variants with five types of transcriptomic phenotypes in 34 tissues. We evaluate tissue specificity of regulatory effects and elucidate molecular mechanisms of their action using multi-omics data. Leveraging this resource, we decipher regulatory mechanisms underlying 207 pig complex phenotypes and demonstrate the similarity of pigs to humans in gene expression and the genetic regulation behind complex phenotypes, supporting the importance of pigs as a human biomedical model.</p

P27Kip1, regulated by glycogen synthase kinase-3β, results in HMBA-induced differentiation of human gastric cancer cells

<p>Abstract</p> <p>Background</p> <p>Gastric cancer is the second most common cause of global cancer-related mortality. Although dedifferentiation predicts poor prognosis in gastric cancer, the molecular mechanism underlying dedifferentiation, which could provide fundamental insights into tumor development and progression, has yet to be elucidated. Furthermore, the molecular mechanism underlying the effects of hexamethylene bisacetamide (HMBA), a recently discovered differentiation inducer, requires investigation and there are no reported studies concerning the effect of HMBA on gastric cancer.</p> <p>Methods</p> <p>Based on the results of FACS analysis, the levels of proteins involved in the cell cycle or apoptosis were determined using western blotting after single treatments and sequential combinations of HMBA and LiCl. GSK-3β and proton pump were investigated by western blotting after up-regulating Akt expression by Ad-Akt infection. To investigate the effects of HMBA on protein localization and the activities of GSK-3β, CDK2 and CDK4, kinase assays, immunoprecipitation and western blotting were performed. In addition, northern blotting and RNase protection assays were carried out to determine the functional concentration of HMBA.</p> <p>Results</p> <p>HMBA increased p27Kip1 expression and induced cell cycle arrest associated with gastric epithelial cell differentiation. In addition, treating gastric-derived cells with HMBA induced G0/G1 arrest and up-regulation of the proton pump, a marker of gastric cancer differentiation. Moreover, treatment with HMBA increased the expression and activity of GSK-3β in the nucleus but not the cytosol. HMBA decreased CDK2 activity and induced p27Kip1 expression, which could be rescued by inhibition of GSK-3β. Furthermore, HMBA increased p27Kip1 binding to CDK2, and this was abolished by GSK-3β inhibition.</p> <p>Conclusions</p> <p>The results presented herein suggest that GSK-3β functions by regulating p27Kip1 assembly with CDK2, thereby playing a critical role in G0/G1 arrest associated with HMBA-induced gastric epithelial cell differentiation.</p

Improved representation of volcanic sulfur dioxide depletion in Lagrangian transport simulations: a case study with MPTRAC v2.4

The lifetime of sulfur dioxide (SO2) in the Earth's atmosphere varies from orders of hours to weeks, mainly depending on whether cloud water is present or not. The volcanic eruption on Ambae Island, Vanuatu, in July 2018 injected a large amount of SO2 into the upper troposphere and lower stratosphere (UT/LS) region with abundant cloud cover. In-cloud removal is therefore expected to play an important role during long-range transport and dispersion of SO2. In order to better represent the rapid decay processes of SO2 observed by the Atmospheric Infrared Sounder (AIRS) and the TROPOspheric Monitoring Instrument (TROPOMI) in Lagrangian transport simulations, we simulate the SO2 decay in a more realistic manner compared to our earlier work, considering gas-phase hydroxyl (OH) chemistry, aqueous-phase hydrogen peroxide (H2O2) chemistry, wet deposition, and convection. The either newly developed or improved chemical and physical modules are implemented in the Lagrangian transport model Massive-Parallel Trajectory Calculations (MPTRAC) and tested in a case study for the July 2018 Ambae eruption. To access the dependencies of the SO2 lifetime on the complex atmospheric conditions, sensitivity tests are conducted by tuning the control parameters, e.g., by changing the release height, the predefined OH climatology data, the cloud pH value, the cloud cover, and other variables. Wet deposition and aqueous-phase H2O2 oxidation remarkably increased the decay rate of the SO2 total mass, which leads to a rapid and more realistic depletion of the Ambae plume. The improved representation of chemical and physical SO2 loss processes described here is expected to lead to more realistic Lagrangian transport simulations of volcanic eruption events with MPTRAC in future work

ALDB: A Domestic-Animal Long Noncoding RNA Database

<div><p>Background</p><p>Long noncoding RNAs (lncRNAs) have attracted significant attention in recent years due to their important roles in many biological processes. Domestic animals constitute a unique resource for understanding the genetic basis of phenotypic variation and are ideal models relevant to diverse areas of biomedical research. With improving sequencing technologies, numerous domestic-animal lncRNAs are now available. Thus, there is an immediate need for a database resource that can assist researchers to store, organize, analyze and visualize domestic-animal lncRNAs.</p><p>Results</p><p>The domestic-<b>a</b>nimal <b>l</b>ncRNA <b>d</b>ata<b>b</b>ase, named ALDB, is the first comprehensive database with a focus on the domestic-animal lncRNAs. It currently archives 12,103 pig intergenic lncRNAs (lincRNAs), 8,923 chicken lincRNAs and 8,250 cow lincRNAs. In addition to the annotations of lincRNAs, it offers related data that is not available yet in existing lncRNA databases (lncRNAdb and NONCODE), such as genome-wide expression profiles and animal quantitative trait loci (QTLs) of domestic animals. Moreover, a collection of interfaces and applications, such as the Basic Local Alignment Search Tool (BLAST), the Generic Genome Browser (GBrowse) and flexible search functionalities, are available to help users effectively explore, analyze and download data related to domestic-animal lncRNAs.</p><p>Conclusions</p><p>ALDB enables the exploration and comparative analysis of lncRNAs in domestic animals. A user-friendly web interface, integrated information and tools make it valuable to researchers in their studies. ALDB is freely available from <a href="http://res.xaut.edu.cn/aldb/index.jsp" target="_blank">http://res.xaut.edu.cn/aldb/index.jsp</a>.</p></div

The Intra-Seasonal Oscillation of Precipitation δ<SUP>18</SUP>O Over the Asian Equatorial and Monsoon Regions

International audienceWater isotopes-climate correlations are used to reconstruct paleoclimate from various natural archives. Intra-seasonal oscillation is one of the major atmospheric patterns that modulate the ratio of precipitation isotope in low latitudes, yet their spatial and temporal distribution patterns are unclear. Here we presented a detailed analysis of how the intra-seasonal oscillations (MJO, Madden-Julian Oscillation, and BSISO, Boreal Summer Intra-seasonal Oscillation) modulate precipitation δ18O and vapor δ18O over the Asian monsoon region and the equatorial region. This analysis found consistent intra-seasonal variations between the ISO and rain δ18O. We interpret it as the ISO regulating the active and inactive convective systems on the regional scale, leading to the intra-seasonal oscillations in precipitation δ18O, with amplitudes from 4‰ up to 15‰. The MJO (BSISO) leads to eastward (northeastward) propagation of δ18O intra-seasonal oscillations in the Asian equatorial (monsoon) region, coinciding with the spatial patterns of OLR oscillations, reflecting the response of precipitation/vapor δ18O to the oscillation of large-scale convective activity or accumulated depletion of regional precipitation. We proved that the amplitudes of intra-seasonal variation of precipitation δ18O are comparable to seasonal variations, and both of them are the main patterns for precipitation δ18O in study regions. Our results are conducive to the accurate interpretation of δ18O in climate proxies such as precipitation, ice cores, tree cellulose, cave stalagmites, et al. on the intra-seasonal scale in this region

Screenshot of the search pages.

<p>(<b>A</b>) Search for transcripts or genes by their ids or names. (<b>B</b>) Basic information for a gene. (<b>C</b>) Basic information for a transcript. (<b>D</b>) The expression levels of genes in various tissue samples. (<b>E</b>) About ten genes adjacent to the current gene are represented. (<b>F</b>) The QTLs which overlap with the current gene or transcript. (<b>G</b>) Search for transcripts or genes by genomic region. (<b>H</b>) Search for neighboring lncRNAs of protein-coding genes.</p

Comparison between ALDB and related databases.

<p>* The number of domestic animal lncRNA transcripts.</p><p>** 16,188 chicken lncRNA transcripts were gathered from an unpublished source.</p><p>Comparison between ALDB and related databases.</p