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Single-cell RNA-sequencing (scRNA-seq) has become a powerful tool for biomedical research by providing a variety of valuable information with the advancement of computational tools. Lineage analysis based on scRNA-seq provides key insights into the fate of individual cells in various systems. However, such analysis is limited by several technical challenges. On top of the considerable computational expertise and resources, these analyses also require specific types of matching data such as exogenous barcode information or bulk assay for transposase-accessible chromatin with high throughput sequencing (ATAC-seq) data. To overcome these technical challenges, we developed a user-friendly computational algorithm called "LINEAGE" (label-free identification of endogenous informative single-cell mitochondrial RNA mutation for lineage analysis). Aiming to screen out endogenous markers of lineage located on mitochondrial reads from label-free scRNA-seq data to conduct lineage inference, LINEAGE integrates a marker selection strategy by feature subspace separation and de novo "low cross-entropy subspaces" identification. In this process, the mutation type and subspace-subspace "cross-entropy" of features were both taken into consideration. LINEAGE outperformed three other methods, which were designed for similar tasks as testified with two standard datasets in terms of biological accuracy and computational efficiency. Applied on a label-free scRNA-seq dataset of BRAF-mutated cancer cells, LINEAGE also revealed genes that contribute to BRAF inhibitor resistance. LINEAGE removes most of the technical hurdles of lineage analysis, which will remarkably accelerate the discovery of the important genes or cell-lineage clusters from scRNA-seq data.

Researchers commonly anneal metals, alloys, and semiconductors to repair defects and improve microstructures via recrystallization. Theoretical studies indicate simulated annealing on biological macromolecules helps predict the final structures with minimum free energy. Experimental validation of this homogenizing effect and further exploration of its applications are fascinating scientific questions that remain elusive. Here, we chose the apo-state 70S ribosome from Escherichia coli as a model, wherein the 30S subunit undergoes a thermally driven inter-subunit rotation and exhibits substantial structural flexibility as well as distinct free energy. We experimentally demonstrate that annealing at a fast cooling rate enhances the 70S ribosome homogeneity and improves local resolution on the 30S subunit. After annealing, the 70S ribosome is in a nonrotated state with respect to corresponding intermediate structures in unannealed or heated ribosomes, and exhibits a minimum energy in the free energy landscape. One can readily crystallize these minimum-energy ribosomes, which have great potential for synchronizing proteins on a single-molecule level. Our experimental results are consistent with theoretical analysis on the temperature-dependent Boltzmann distribution, and offer a facile yet robust approach to enhance protein stability, which is ideal for high-resolution cryogenic electron microscopy. Beyond structure determination, annealing can be extended to study protein folding and explore conformational and energy landscape.Significance statementIn metallurgy, annealing heats a metal or alloy to a predetermined temperature, holding for a certain time, and then cooling to room temperature to change the physical and sometimes also the chemical properties of the material. Researchers introduce the similar concept as simulated annealing to predict minimum-energy conformations of biological macromolecules. In this work, we experimentally verify that annealing at a fast cooling rate can synchronize the 70S ribosome into a nonrotated state with a minimum energy in the free energy landscape. Our results not only offer a facile yet robust approach to stabilize proteins for high-resolution structural analysis, but also contribute to the understanding of protein folding and temperature adaptation.

In comparison to mouse, the developmental process of human islets has not been properly elucidated. The advancement of single cell RNA-seq technology enables us to study the properties of alpha and beta cells at single cell resolution. By using mitochondrial genome variants as endogenous lineage-tracing markers, we found that human alpha and beta cells have different lineage features. This finding suggests specific endocrine progenitors for alpha and beta cells, which is different from mouse islet cells. This strategy was also applied to a study of chemically-induced islet cell reprogramming and was used to help identify artemether-induced alpha-to-beta trans-differentiation in human islets. The computational results of this study will inspire future studies to establish, maintain, and expand beta cell-specific progenitors in vitro and in vivo.

LncRNAs are emerging as integral functional and regulatory components of normal biological activities and are now considered as critically involved in the development of different diseases including cancer. In this review, we summarized recent findings on maternally expressed gene 3 (MEG3), a noncoding lncRNA, locates in the imprinted DLK1-MEG3 locus on human chromosome 14q32.3 region. MEG3 is expressed in normal tissues but is either lost or decreased in many human tumors and tumor derived cell lines. Studies have demonstrated that MEG3 is associated with cancer initiation, progression, metastasis and chemo-resistance. MEG3 may affect the activities of TP53, MDM2, GDF15, RB1 and some other key cell cycle regulators. In addition, the level of MEG3 showed good correlation with cancer clinicopathological grade. In summary, MEGs is an RNA-based tumor suppressor and is involved in the etiology, progression, and chemosensitivity of cancers. The alteration of MEG3 levels in various cancers suggested the possibility of using MEG3 level for cancer diagnosis and prognosis.

Activation of the innate immune system before the invasion of pathogens is a promising way to improve the resistance of plant against infection while reducing the use of agricultural chemicals. Although several elicitors were used to induce the resistance of potato plant to microbial pathogen infection, the role of curdlan oligosaccharide (CurdO) has not been established. In the current study, the defense responses were investigated at biochemical and proteomic levels to elucidate the elicitation effect of CurdOs in foliar tissues of potato (Solanum tuberosum L. cv. McCain G1). The results indicate that the CurdOs exhibit activation effect on the early- and late-defense responses in potato leaves. In addition, glucopentaose was proved to be the shortest active curdlan molecule based on the accumulation of H₂O₂ and salicylic acid and the activities of phenylalanine amino-lyase, β-1,3-glucanase and chitinase. The 2D-PAGE analysis reveals that CurdOs activate the integrated response reactions in potato cells, as a number of proteins with various functions are up-regulated including disease/defense, metabolism, transcription, and cell structure. The pathogenesis assay shows that the ratio of lesion area of potato leaf decreased from 15.82%±5.44% to 7.79%±3.03% when the plants were treated with CurdOs 1 day before the infection of Phytophthora infestans. Furthermore, the results on potato yield and induction reactions indicate that the defense responses induced by CurdOs lasted for short period of time but disappeared gradually.