Systematic and integrated analysis of tRNA-derived small RNAs reveals novel potential pathogenesis targets of sarcoidosis

The pathogenesis of sarcoidosis, which involves several systems, is unclear, and its pathological type is non-caseating epithelioid granulomas. tRNA-derived small RNA (tsRNA) is a novel class of short non-coding RNAs with potential regulatory functions. However, whether tsRNA contributes to sarcoidosis pathogenesis remains unclear. Deep sequencing technology was used to identify alterations in tsRNA expression profiles between patients with sarcoidosis and healthy controls. A total of 360 tsRNAs were identified for exact matches. Among them, the expression of three tRNAs (tiRNA-Glu-TTC-001, tiRNA-Lys-CTT-003, and tRF-Ser-TGA-007) was markedly regulated in sarcoidosis and validated by quantitative real-time polymerase chain reaction. The expression of various tsRNAs was significantly correlated with age, the number of affected systems, and calcium levels in the blood. Additionally, target prediction and bioinformatics analyses revealed that these tsRNAs may play roles in chemokine, cAMP, cGMP-PKG, retrograde endorphin, and FoxO signalling pathways. The Cytoscape software was used for visual analysis to obtain 10 hub genes of each target tsRNA. Among the hub genes, APP, PRKACB, ARRB2, and NR5A1 finding may participate in the occurrence and development of sarcoidosis through immune inflammation. This study provides novel insights to explore tsRNA as a novel and efficacious pathogenic target of sarcoidosis.

Genome-Wide Transcriptional Changes of Rhodosporidium kratochvilovae at Low Temperature

Rhodosporidium kratochvilovae strain YM25235 is a cold-adapted oleaginous yeast strain that can grow at 15°C. It is capable of producing polyunsaturated fatty acids. Here, we used the Nanopore Platform to first assemble the R. kratochvilovae strain YM25235 genome into a 23.71 Mb size containing 46 scaffolds and 8,472 predicted genes. To explore the molecular mechanism behind the low temperature response of R. kratochvilovae strain YM25235, we analyzed the RNA transcriptomic data from low temperature (15°C) and normal temperature (30°C) groups using the next-generation deep sequencing technology (RNA-seq). We identified 1,300 differentially expressed genes (DEGs) by comparing the cultures grown at low temperature (15°C) and normal temperature (30°C) transcriptome libraries, including 553 significantly upregulated and 747 significantly downregulated DEGs. Gene ontology and pathway enrichment analysis revealed that DEGs were primarily related to metabolic processes, cellular processes, cellular organelles, and catalytic activity, whereas the overrepresented pathways included the MAPK signaling pathway, metabolic pathways, and amino sugar and nucleotide sugar metabolism. We validated the RNA-seq results by detecting the expression of 15 DEGs using qPCR. This study provides valuable information on the low temperature response of R. kratochvilovae strain YM25235 for further research and broadens our understanding for the response of R. kratochvilovae strain YM25235 to low temperature.

Circular RNAs’ cap-independent translation protein and its roles in carcinomas

Circular RNAs a kind of covalently closed RNA and widely expressed in eukaryotes. CircRNAs are involved in a variety of physiological and pathological processes, but their regulatory mechanisms are not fully understood. Given the development of the RNA deep-sequencing technology and the improvement of algorithms, some CircRNAs are discovered to encode proteins through the cap-independent mechanism and participate in the important process of tumorigenesis and development. Based on an overview of CircRNAs, this paper summarizes its translation mechanism and research methods, and reviews the research progress of CircRNAs translation in the field of oncology in recent years. Moreover, this paper aims to provide new ideas for tumor diagnosis and treatment through CircRNAs translation.

MiR-103a promotes tumour growth and influences glucose metabolism in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a common and high-mortality cancer worldwide. Numerous microRNAs have crucial roles in the progression of different cancers. However, identifying the important microRNAs and the target biological function of the microRNA in HCC progression is difficult. In this study, we selected highly expressed microRNAs with different read counts as candidate microRNAs and then tested whether the microRNAs were differentially expressed in HCC tumour tissues, and we found that their expression was related to the HCC prognosis. Then, we investigated the effects of microRNAs on the cell growth and mobility of HCC using a real-time cell analyser (RTCA), colony formation assay and subcutaneous xenograft models. We further used deep-sequencing technology and bioinformatic analyses to evaluate the main functions of the microRNAs. We found that miR-103a was one of the most highly expressed microRNAs in HCC tissues and that it was upregulated in HCC tissue compared with the controls. In addition, high miR-103a expression was associated with poor patient prognosis, and its overexpression promoted HCC cell growth and mobility. A functional enrichment analysis showed that miR-103a mainly promoted glucose metabolism and inhibited cell death. We validated this analysis, and the data showed that miR-103a promoted glucose metabolism-likely function and directly inhibited cell death via ATP11A and EIF5. Therefore, our study revealed that miR-103a may act as a key mediator in HCC progression.

Identification of Plant DNA in Adults of the Phytoplasma Vector Cacopsylla picta Helps Understanding Its Feeding Behavior

Apple proliferation is an economically important disease and a threat for commercial apple cultivation. The causative pathogen, the bacterium ‘Candidatus Phytoplasma mali’, is mainly transmitted by Cacopsylla picta, a phloem-feeding insect that develops on the apple tree (Malus spp.). To investigate the feeding behavior of adults of the phytoplasma vector Cacopsylla picta in more detail, we used deep sequencing technology to identify plant-specific DNA ingested by the insect. Adult psyllids were collected in different apple orchards in the Trentino-South Tyrol region of northern Italy. DNA from the whole body of the insect was extracted and analyzed for the presence of plant DNA by performing PCR with two plant-specific primers that target the chloroplast regions trnH-psbA and rbcLa. DNA from 23 plant genera (trnH) and four plant families (rbcLa) of woody and herbaceous plant taxa was detected. Up to six and three plant genera and families, respectively, could be determined in single specimens. The results of this study contribute to a better understanding of the feeding behavior of adult Cacopsylla picta.

Analysis of the microRNA expression profiles of chicken dendritic cells in response to H9N2 avian influenza virus infection

MicroRNA (miRNA) plays a key role in virus-host interactions. Here, we employed deep sequencing technology to determine cellular miRNA expression profiles in chicken dendritic cells infected with H9N2 avian influenza virus (AIV). A total of 66 known and 36 novel miRNAs were differently expressed upon H9N2 infection, including 72 up-regulated and 30 down-regulated miRNAs. Functional analysis showed that the predicted targets of these miRNAs were significantly enriched in several pathways including endocytosis, notch, lysosome, p53, RIG-I-like and NOD-like receptor signaling pathways. These data provide valuable information for further investigating the roles of miRNA in AIV pathogenesis and host defense response.

Expansion and Refinement of Deep Sequence-Coupled Biopanning Technology for Epitope-Specific Antibody Responses in Human Serum

Identifying the specific epitopes targeted by antibodies elicited in response to infectious diseases is important for developing vaccines and diagnostics. However, techniques for broadly exploring the specificity of antibodies in a rapid manner are lacking, limiting our ability to quickly respond to emerging viruses. We previously reported a technology that couples deep sequencing technology with a bacteriophage MS2 virus-like particle (VLP) peptide display platform for identifying pathogen-specific antibody responses. Here, we describe refinements that expand the number of patient samples that can be processed at one time, increasing the utility of this technology for rapidly responding to emerging infectious diseases. We used dengue virus (DENV) as a model system since much is already known about the antibody response. Sera from primary DENV-infected patients (n = 28) were used to pan an MS2 bacteriophage VLP library displaying all possible 10-amino-acid peptides from the DENV polypeptide. Selected VLPs were identified by deep sequencing and further investigated by enzyme-linked immunosorbent assay. We identified previously described immunodominant regions of envelope and nonstructural protein-1, as well as a number of other epitopes. Our refinement of the deep sequence-coupled biopanning technology expands the utility of this approach for rapidly investigating the specificity of antibody responses to infectious diseases.

Dynamic Transcriptional Profiles of Arabidopsis thaliana Infected by Tomato spotted wilt virus

Tomato spotted wilt virus (TSWV) is a negative-stranded RNA virus that infects hundreds of plant species, causing great economic loss. Infected Arabidopsis thaliana plants develop symptoms including chlorosis and wilt, which can lead to cell death. From 9 to 15 days after TSWV infection, symptoms progress through a three-stage process of appearance, severity, and death. In this study, deep sequencing technology was first used to explore gene expression in response to TSWV infection in model plant A. thaliana at different symptom development stages. We found that plant immune defense and protein degradation are induced by TSWV infection and that both inductions became stronger over time. The photosynthesis pathway was attenuated with TSWV infection. Cell wall metabolism had a large extent of downregulation while some genes were upregulated. These results illustrate the dynamic nature of TSWV infection in A. thaliana at the whole-transcriptome level. The link between biological processes and subpathway metabolism was further analyzed. Our study provides new insight into host regulatory networks and dynamic processes in response to TSWV infection.

Comparison of the pituitary gland transcriptome in pregnant and non-pregnant goats (Capra hircus)

Pregnancy is strictly regulated by neuronal and hormonal factors with an essential role being played by the pituitary gland. We screened for differentially expressed genes (DEGs) in the pituitary that function in goat gestational development. Pregnant (AWGp) and non-pregnant Anhui white goats (AWGn) were analysed by deep-sequencing technology. A total of 12 774 092 and 13 872 327 clear reads were obtained in the AWGp and AWGn libraries, respectively. A total of 2593 genes were labelled as significantly differentially expressed in AWGp compared to AWGn, including 2158 upregulated genes and 435 downregulated genes. These genes included follicle stimulating hormone beta (FSHB) and luteinizing hormone beta (LHB), which showed an involvement in reproductive regulation and downregulation (AWGp vs AWGn). Quantitative real-time PCR (qPCR) results validated the DEG data. Subsequent gene ontology analysis indicated that a large number of these DEGs function in cellular processes, cell structures, and cell binding. The DEGs were also found by Kyoto Gene and Genomic Encyclopaedia analysis to be significantly enriched in 54 pathways, including the GnRH and TGF-beta signalling pathways that affect cell proliferation and hormone secretion. These data also identify genes that may play a role in pregnancy and reproduction in the goat and thus provide avenues for future research.

Identification and characterization of Coronaviridae genomes from Vietnamese bats and rats based on conserved protein domains

The Coronaviridae family of viruses encompasses a group of pathogens with a zoonotic potential as observed from previous outbreaks of the severe acute respiratory syndrome coronavirus and Middle East respiratory syndrome coronavirus. Accordingly, it seems important to identify and document the coronaviruses in animal reservoirs, many of which are uncharacterized and potentially missed by more standard diagnostic assays. A combination of sensitive deep sequencing technology and computational algorithms is essential for virus surveillance, especially for characterizing novel- or distantly related virus strains. Here, we explore the use of profile Hidden Markov Model-defined Pfam protein domains (Pfam domains) encoded by new sequences as a Coronaviridae sequence classification tool. The encoded domains are used first in a triage to identify potential Coronaviridae sequences and then processed using a Random Forest method to classify the sequences to the Coronaviridae genus level. The application of this algorithm on Coronaviridae genomes assembled from agnostic deep sequencing data from surveillance of bats and rats in Dong Thap province (Vietnam) identified thirty-four Alphacoronavirus and eleven Betacoronavirus genomes. This collection of bat and rat coronaviruses genomes provided essential information on the local diversity of coronaviruses and substantially expanded the number of coronavirus full genomes available from bat and rats and may facilitate further molecular studies on this group of viruses.