Highlights d 11,394 proteins are quantified in autopsy samples from 7 organs in 19 COVID-19 patients d Elevated expression of cathepsin L1 is detected in the COVID-19 lung tissue d Dysregulation of angiogenesis, coagulation, and fibrosis is detected in multiple organs d Systemic metabolic dysregulation is detected in multiple organs

Natural antisense transcripts (NATs), as one type of regulatory RNAs, occur prevalently in plant genomes and play significant roles in physiological and pathological processes. Although their important biological functions have been reported widely, a comprehensive database is lacking up to now. Consequently, we constructed a plant NAT database (PlantNATsDB) involving approximately 2 million NAT pairs in 69 plant species. GO annotation and high-throughput small RNA sequencing data currently available were integrated to investigate the biological function of NATs. PlantNATsDB provides various user-friendly web interfaces to facilitate the presentation of NATs and an integrated, graphical network browser to display the complex networks formed by different NATs. Moreover, a ‘Gene Set Analysis’ module based on GO annotation was designed to dig out the statistical significantly overrepresented GO categories from the specific NAT network. PlantNATsDB is currently the most comprehensive resource of NATs in the plant kingdom, which can serve as a reference database to investigate the regulatory function of NATs. The PlantNATsDB is freely available at http://bis.zju.edu.cn/pnatdb/.

The limited molecular classifications and disease signatures of osteoarthritis (OA) impede the development of prediagnosis and targeted therapeutics for OA patients. To classify and understand the subtypes of OA, we collected three types of tissue including cartilage, subchondral bone, and synovium from multiple clinical centers and constructed an extensive transcriptome atlas of OA patients. By applying unsupervised clustering analysis to the cartilage transcriptome, OA patients were classified into four subtypes with distinct molecular signatures: a glycosaminoglycan metabolic disorder subtype (C1), a collagen metabolic disorder subtype (C2), an activated sensory neuron subtype (C3), and an inflammation subtype (C4). Through ligand-receptor crosstalk analysis of the three knee tissue types, we linked molecular functions with the clinical symptoms of different OA subtypes. For example, the Gene Ontology functional term of vasculature development was enriched in the subchondral bone-cartilage crosstalk of C2 and the cartilage-subchondral bone crosstalk of C4, which might lead to severe osteophytes in C2 patients and apparent joint space narrowing in C4 patients. Based on the marker genes of the four OA subtypes identified in this study, we modeled OA subtypes with two independent published RNA-seq datasets through random forest classification. The findings of this work contradicted traditional OA diagnosis by medical imaging and revealed distinct molecular subtypes in knee OA patients, which may allow for precise diagnosis and treatment of OA.

Natural antisense transcripts (NATs) are endogenous transcripts that can form double-stranded RNA structures. Many protein-coding genes (PCs) and non-protein-coding genes (NPCs) tend to form cis-NATs and trans-NATs, respectively. In this work, we identified 4,080 cis-NATs and 2,491 trans-NATs genome-widely in Arabidopsis. Of these, 5,385 NAT-siRNAs were detected from the small RNA sequencing data. NAT-siRNAs are typically 21nt, and are processed by Dicer-like 1 (DCL1)/DCL2 and RDR6 and function in epigenetically activated situations, or 24nt, suggesting these are processed by DCL3 and RDR2 and function in environment stress. NAT-siRNAs are significantly derived from PC/PC pairs of trans-NATs and NPC/NPC pairs of cis-NATs. Furthermore, NAT pair genes typically have similar pattern of epigenetic status. Cis-NATs tend to be marked by euchromatic modifications, whereas trans-NATs tend to be marked by heterochromatic modifications.

The performance of data-independent acquisition (DIA) mass spectrometry (MS) depends on the separation efficiency of peptide precursors. In Orbitrap-based mass spectrometers, separation efficiency of peptide precursors is limited by the relatively slow scanning rate compared to time of flight (TOF)-based MS. Here, we present PulseDIA, a multi-injection gas-phase fractionation (GPF) strategy for enhanced DIA-MS. This is achieved by equally dividing the conventional DIA analysis covering the entire mass range into multiple injections for DIA analyses with complementary windows. Using mouse liver digests, the PulseDIA method identified up to 50% more peptides and 29% more protein groups than that by conventional DIA with the same length of effective gradient time. Compared to conventional multi-injection GPF, PusleDIA exhibited higher flexibility and identified up to 18% more peptides and 8% more protein groups using two injections. The gain of peptides per effective time unit was the highest in PulseDIA compared to conventional DIA and GPF. We further applied the PulseDIA method to profile the proteome of 18 human tissue samples (benign and malignant) from nine cholangiocarcinoma (CCA) patients. PulseDIA identified 7796 protein groups in these CCA samples, with a 14% increase of protein group identification compared to the conventional DIA method. The missing value for protein matrix dropped by 7% using PulseDIA compared to DIA. A total of 681 significantly altered proteins were detected in CCA samples using PulseDIA, including several dysregulated proteins, which were absent in the conventional DIA analysis. Taken together, we present PulseDIA as an enhanced DIA-MS method with improved sensitivity and reproducibility.

Competition for microRNA (miRNA) binding between RNA molecules has emerged as a novel mechanism for the regulation of eukaryotic gene expression. Competing endogenous RNA (ceRNA) can act as decoys for miRNA binding, thereby forming a ceRNA network by regulating the abundance of other RNA transcripts which share the same or similar microRNA response elements. Although this type of RNA cross talk was first described in Arabidopsis, and was subsequently shown to be active in animal models, there is no database collecting potential ceRNA data for plants. We have developed a Plant ceRNA database (PceRBase, http://bis.zju.edu.cn/pcernadb/index.jsp) which contains potential ceRNA target-target, and ceRNA target-mimic pairs from 26 plant species. For example, in Arabidopsis lyrata, 311 candidate ceRNAs are identified which could affect 2646 target–miRNA–target interactions. Predicted pairing structure between miRNAs and their target mRNA transcripts, expression levels of ceRNA pairs and associated GO annotations are also stored in the database. A web interface provides convenient browsing and searching for specific genes of interest. Tools are available for the visualization and enrichment analysis of genes in the ceRNA networks. Moreover, users can use PceRBase to predict novel competing mimic-target and target–target interactions from their own data.

We report and evaluated a microflow, single-shot, short gradient SWATH MS method intended to accelerate the discovery and verification of protein biomarkers in clinical specimens. The method uses 15-min gradient microflow-LC peptide separation, an optimized SWATH MS window configuration and OpenSWATH software for data analysis.We applied the method to a cohort 204 of FFPE prostate tissue samples from 58 prostate cancer patients and 10 prostatic hyperplasia patients. Altogether we identified 27,976 proteotypic peptides and 4,043 SwissProt proteins from these 204 samples. Compared to a reference SWATH method with 2-hour gradient the accelerated method consumed only 27% instrument time, quantified 80% proteins and showed reduced batch effects. 3,800 proteins were quantified by both methods in two different instruments with relatively high consistency (r = 0.77). 75 proteins detected by the accelerated method with differential abundance between clinical groups were selected for further validation. A shortlist of 134 selected peptide precursors from the 75 proteins were analyzed using MRM-HR, exhibiting high quantitative consistency with the 15-min SWATH method (r = 0.89) in the same sample set.We further verified the capacity of these 75 proteins in separating benign and malignant tissues (AUC = 0.99) in an independent prostate cancer cohort (n=154).Overall our data show that the single-shot short gradient microflow-LC SWATH MS method achieved about 4-fold acceleration of data acquisition with reduced batch effect and a moderate level of protein attrition compared to a standard SWATH acquisition method.Finally, the results showed comparable ability to separate clinical groups.

Small RNAs (sRNAs), largely known as microRNAs (miRNAs) and short interfering RNAs (siRNAs), emerged as the critical components of genetic and epigenetic regulation in eukaryotic genomes. In animals, a sizable portion of miRNAs reside within the introns of protein-coding genes, designated as mirtron genes. Recently, high-throughput sequencing (HTS) revealed a huge amount of sRNAs that derived from introns in plants, such as the monocot rice (Oryza sativa). However, the biogenesis and the biological functions of this kind of sRNAs remain elusive. Here, we performed a genome-scale survey of intron-derived sRNAs in rice based on HTS data. Several introns were found to have great potential to form internal hairpin structures, and the short hairpins could generate miRNAs while the larger ones could produce siRNAs. Furthermore, 22 introns, termed ''sirtrons,'' were identified from the rice protein-coding genes. The single-stranded sirtrons produced a diverse set of siRNAs from long hairpin structures. These sirtron-derived siRNAs are dominantly 21 nt, 22 nt, and 24 nt in length, whose production relied on DCL4, DCL2, and DCL3, respectively. We also observed a strong tendency for the sirtron-derived siRNAs to be coexpressed with their host genes. Finally, the 24-nt siRNAs incorporated with Argonaute 4 (AGO4) could direct DNA methylation on their host genes. In this regard, homeostatic self-regulation between intron-derived siRNAs and their host genes was proposed.