miRecords: an integrated resource for microRNA–target interactions

MicroRNAs (miRNAs) are an important class of small noncoding RNAs capable of regulating other genes’ expression. Much progress has been made in computational target prediction of miRNAs in recent years. More than 10 miRNA target prediction programs have been established, yet, the prediction of animal miRNA targets remains a challenging task. We have developed miRecords, an integrated resource for animal miRNA–target interactions. The Validated Targets component of this resource hosts a large, high-quality manually curated database of experimentally validated miRNA–target interactions with systematic documentation of experimental support for each interaction. The current release of this database includes 1135 records of validated miRNA–target interactions between 301 miRNAs and 902 target genes in seven animal species. The Predicted Targets component of miRecords stores predicted miRNA targets produced by 11 established miRNA target prediction programs. miRecords is expected to serve as a useful resource not only for experimental miRNA researchers, but also for informatics scientists developing the next-generation miRNA target prediction programs. The miRecords is available at http://miRecords.umn.edu/miRecords

Clustered microRNAs' coordination in regulating protein-protein interaction network

<p>Abstract</p> <p>Background</p> <p>MicroRNAs (miRNAs), a growing class of small RNAs with crucial regulatory roles at the post-transcriptional level, are usually found to be clustered on chromosomes. However, with the exception of a few individual cases, so far little is known about the functional consequence of this conserved clustering of miRNA loci. In animal genomes such clusters often contain non-homologous miRNA genes. One hypothesis to explain this heterogeneity suggests that clustered miRNAs are functionally related by virtue of co-targeting downstream pathways.</p> <p>Results</p> <p>Integrating of miRNA cluster information with protein protein interaction (PPI) network data, our research supports the hypothesis of the functional coordination of clustered miRNAs and links it to the topological features of miRNAs' targets in PPI network. Specifically, our results demonstrate that clustered miRNAs jointly regulate proteins in close proximity of the PPI network. The possibility that two proteins yield to this coordinated regulation is negatively correlated with their distance in PPI network. Guided by the knowledge of this preference, we found several network communities enriched with target genes of miRNA clusters. In addition, our results demonstrate that the variance of this propensity can also partly be explained by protein's connectivity and miRNA's conservation.</p> <p>Conclusion</p> <p>In summary, this work supports the hypothesis of intra-cluster coordination and investigates the extent of this coordination.</p

Meta-prediction of protein subcellular localization with reduced voting

Meta-prediction seeks to harness the combined strengths of multiple predicting programs with the hope of achieving predicting performance surpassing that of all existing predictors in a defined problem domain. We investigated meta-prediction for the four-compartment eukaryotic subcellular localization problem. We compiled an unbiased subcellular localization dataset of 1693 nuclear, cytoplasmic, mitochondrial and extracellular animal proteins from Swiss-Prot 50.2. Using this dataset, we assessed the predicting performance of 12 predictors from eight independent subcellular localization predicting programs: ELSPred, LOCtree, PLOC, Proteome Analyst, PSORT, PSORT II, SubLoc and WoLF PSORT. Gorodkin correlation coefficient (GCC) was one of the performance measures. Proteome Analyst is the best individual subcellular localization predictor tested in this four-compartment prediction problem, with GCC = 0.811. A reduced voting strategy eliminating six of the 12 predictors yields a meta-predictor (RAW-RAG-6) with GCC = 0.856, substantially better than all tested individual subcellular localization predictors (P = 8.2 × 10−6, Fisher's Z-transformation test). The improvement in performance persists when the meta-predictor is tested with data not used in its development. This and similar voting strategies, when properly applied, are expected to produce meta-predictors with outstanding performance in other life sciences problem domains

Genome-wide identification of TPS and TPP genes in cultivated peanut (Arachis hypogaea) and functional characterization of AhTPS9 in response to cold stress

IntroductionTrehalose is vital for plant metabolism, growth, and stress resilience, relying on Trehalose-6-phosphate synthase (TPS) and Trehalose-6-phosphate phosphatase (TPP) genes. Research on these genes in cultivated peanuts (Arachis hypogaea) is limited.MethodsThis study employed bioinformatics to identify and analyze AhTPS and AhTPP genes in cultivated peanuts, with subsequent experimental validation of AhTPS9’s role in cold tolerance.ResultsIn the cultivated peanut genome, a total of 16 AhTPS and 17 AhTPP genes were identified. AhTPS and AhTPP genes were observed in phylogenetic analysis, closely related to wild diploid peanuts, respectively. The evolutionary patterns of AhTPS and AhTPP genes were predominantly characterized by gene segmental duplication events and robust purifying selection. A variety of hormone-responsive and stress-related cis-elements were unveiled in our analysis of cis-regulatory elements. Distinct expression patterns of AhTPS and AhTPP genes across different peanut tissues, developmental stages, and treatments were revealed, suggesting potential roles in growth, development, and stress responses. Under low-temperature stress, qPCR results showcased upregulation in AhTPS genes (AhTPS2-5, AhTPS9-12, AhTPS14, AhTPS15) and AhTPP genes (AhTPP1, AhTPP6, AhTPP11, AhTPP13). Furthermore, AhTPS9, exhibiting the most significant expression difference under cold stress, was obviously induced by cold stress in cultivated peanut, and AhTPS9-overexpression improved the cold tolerance of Arabidopsis by protect the photosynthetic system of plants, and regulates sugar-related metabolites and genes.DiscussionThis comprehensive study lays the groundwork for understanding the roles of AhTPS and AhTPP gene families in trehalose regulation within cultivated peanuts and provides valuable insights into the mechanisms related to cold stress tolerance

Genome-wide analysis reveals regulatory mechanisms and expression patterns of TGA genes in peanut under abiotic stress and hormone treatments

IntroductionThe TGA transcription factors, plays a crucial role in regulating gene expression. In cultivated peanut (Arachis hypogaea), which faces abiotic stress challenges, understanding the role of TGAs is important.MethodsIn this study, we conducted a comprehensive in analysis of the TGA gene family in peanut to elucidate their regulatory mechanisms and expression patterns under abiotic stress and hormone treatments. Furthermore, functional studies on the representative AhTGA gene in peanut cultivars were conducted using transgenic Arabidopsis and soybean hair roots.ResultsThe genome-wide analysis revealed that a total of 20 AhTGA genes were identified and classified into five subfamilies. Collinearity analysis revealed that AhTGA genes lack tandem duplication, and their amplification in the cultivated peanut genome primarily relies on the whole-genome duplication of the diploid wild peanut to form tetraploid cultivated peanut, as well as segment duplication between the A and B subgenomes. Promoter and Protein-protein interaction analysis identified a wide range of cis-acting elements and potential interacting proteins associated with growth and development, hormones, and stress responses. Expression patterns of AhTGA genes in different tissues, under abiotic stress conditions for low temperature and drought, and in response to hormonal stimuli revealed that seven AhTGA genes from groups I (AhTGA04, AhTGA14 and AhTGA20) and II (AhTGA07, AhTGA11, AhTGA16 and AhTGA18) are involved in the response to abiotic stress and hormonal stimuli. The hormone treatment results indicate that these AhTGA genes primarily respond to the regulation of jasmonic acid and salicylic acid. Overexpressing AhTGA11 in Arabidopsis enhances resistance to cold and drought stress by increasing antioxidant activities and altering endogenous hormone levels, particularly ABA, SA and JA.DiscussionThe AhTGA genes plays a crucial role in hormone regulation and stress response during peanut growth and development. The findings provide insights into peanut's abiotic stress tolerance mechanisms and pave the way for future functional studies

Advanced Glycation End Products-Induced Activation of Keratinocytes: A Mechanism Underlying Cutaneous Immune Response in Psoriasis

Psoriasis is a common inflammatory skin disease, in which epidermal keratinocytes play a vital role in its pathogenesis by acting both as the responder and as the accelerator to the cutaneous psoriatic immune response. Advanced glycation end products (AGEs) are a class of proinflammatory metabolites that are commonly accumulating in cardiometabolic disorders. Recent studies have also observed the increased level of AGEs in the serum and skin of psoriasis patients, but the role of AGEs in psoriatic inflammation has not been well investigated. In the present study, we initially detected abnormal accumulation of AGEs in epidermal keratinocytes of psoriatic lesions collected from psoriasis patients. Furthermore, AGEs promoted the proliferation of keratinocytes via upregulated Keratin 17 (K17)-mediated p27KIP1 inhibition followed by accelerated cell cycle progression. More importantly, AGEs facilitated the production of interleukin-36 alpha (IL-36α) in keratinocytes, which could enhance T helper 17 (Th17) immune response. In addition, the induction of both K17 and IL-36α by AGEs in keratinocytes was dependent on the activation of signal transducer and activator of transcription 1/3 (STAT1/3) signaling pathways. At last, the effects of AGEs on keratinocytes were mediated by the receptor for AGEs (RAGE). Taken together, these findings support that AGEs potentiate the innate immune function of keratinocytes, which contributes to the formation of psoriatic inflammation. Our study implicates AGEs as a potential pathogenic link between psoriasis and cardiometabolic comorbidities

Protein interaction network of alternatively spliced isoforms from brain links genetic risk factors for autism

Increased risk for autism spectrum disorders (ASD) is attributed to hundreds of genetic loci. The convergence of ASD variants have been investigated using various approaches, including protein interactions extracted from the published literature. However, these datasets are frequently incomplete, carry biases and are limited to interactions of a single splicing isoform, which may not be expressed in the disease-relevant tissue. Here we introduce a new interactome mapping approach by experimentally identifying interactions between brain-expressed alternatively spliced variants of ASD risk factors. The Autism Spliceform Interaction Network reveals that almost half of the detected interactions and about 30% of the newly identified interacting partners represent contribution from splicing variants, emphasizing the importance of isoform networks. Isoform interactions greatly contribute to establishing direct physical connections between proteins from the de novo autism CNVs. Our findings demonstrate the critical role of spliceform networks for translating genetic knowledge into a better understanding of human diseases

Large-scale prediction of long non-coding RNA functions in a coding–non-coding gene co-expression network

Although accumulating evidence has provided insight into the various functions of long-non-coding RNAs (lncRNAs), the exact functions of the majority of such transcripts are still unknown. Here, we report the first computational annotation of lncRNA functions based on public microarray expression profiles. A coding–non-coding gene co-expression (CNC) network was constructed from re-annotated Affymetrix Mouse Genome Array data. Probable functions for altogether 340 lncRNAs were predicted based on topological or other network characteristics, such as module sharing, association with network hubs and combinations of co-expression and genomic adjacency. The functions annotated to the lncRNAs mainly involve organ or tissue development (e.g. neuron, eye and muscle development), cellular transport (e.g. neuronal transport and sodium ion, acid or lipid transport) or metabolic processes (e.g. involving macromolecules, phosphocreatine and tyrosine)

Functional annotation of the cattle genome through systematic discovery and characterization of chromatin states and butyrate-induced variations

The functional annotation of genomes, including chromatin accessibility and modifications, is important for understanding and effectively utilizing the increased amount of genome sequences reported. However, while such annotation has been well explored in a diverse set of tissues and cell types in human and model organisms, relatively little data are available for livestock genomes, hindering our understanding of complex trait variation, domestication, and adaptive evolution. Here, we present the first complete global landscape of regulatory elements in cattle and explore the dynamics of chromatin states in rumen epithelial cells induced by the rumen developmental regulator—butyrate.https://doi.org/10.1186/s12915-019-0687-