SUMMARY Golgi complexes (Golgi) play important roles in the development and function of neurons [1–3]. Not only are Golgi present in the neuronal soma (somal Golgi) but they also exist in the dendrites as Golgi outposts [4–7]. Previous studies have shown that Golgi outposts serve as local microtubule organizing centers [8] and secretory stations in dendrites [6, 9]. It is unknown whether the structure and function of Golgi outposts differ from those of somal Golgi. Here we show in Drosophila that, unlike somal Golgi, the biochemically distinct cis, medial, and trans compartments of Golgi are often disconnected in dendrites in vivo. The Golgi structural protein GM130 is responsible for connecting distinct Golgi compartments in soma and dendritic branch points, and specific distribution of GM130 determines the compartmental organization of dendritic Golgi in dendritic shafts. We further show that compartmental organization regulates the role of Golgi in acentrosomal microtubule growth in dendrites and in dendritic branching. Our study provides insights into the structure and function of dendritic Golgi outposts as well as the regulation of compartmental organization of Golgi in general.

Accurate somatic mutation detection from single-cell DNA sequencing (scDNA-seq) is challenging due to amplification-related artifacts. To reduce this artifact burden, an improved amplification technique, primary template-directed amplification (PTA), was recently introduced. We analyzed whole-genome sequencing data from 52 PTA-amplified single neurons using SCAN2, a new genotyper we developed to leverage mutation signatures and allele balance in identifying somatic single-nucleotide variants (SNVs) and small insertions and deletions (indels) in PTA data. Our analysis confirms an increase in non-clonal somatic mutation in single neurons with age, but revises the estimated rate of this accumulation to be 16 SNVs per year. We also identify artifacts in other amplification methods. Most importantly, we show

Heimuer, Auricularia heimuer, is one of the most famous traditional Chinese foods and medicines, and it is the third most important cultivated mushroom worldwide. The aim of this study is to develop genomic resources for A. heimuer to furnish tools that can be used to study its secondary metabolite production capability, wood degradation ability and biosynthesis of polysaccharides. The genome was obtained from single spore mycelia of the strain Dai 13782 by using combined high-throughput Illumina HiSeq 4000 system with the PacBio RSII long-read sequencing platform. Functional annotation was accomplished by blasting protein sequences with different public available databases to obtain their corresponding annotations. It is 49.76Mb in size with a N50 scaffold size of 1,350,668bp and encodes 16,244 putative predicted genes. This is the first genome-scale assembly and annotation for A. heimuer, which is the third sequenced species in Auricularia.

The advent of single-cell RNA sequencing (scRNA-seq) technologies has revolutionized transcriptomic studies. However, large-scale integrative analysis of scRNA-seq data remains a challenge largely due to unwanted batch effects and the limited transferabilty, interpretability, and scalability of the existing computational methods. We present single-cell Embedded Topic Model (scETM). Our key contribution is the utilization of a transferable neural-network-based encoder while having an interpretable linear decoder via a matrix tri-factorization. In particular, scETM simultaneously learns an encoder network to infer cell type mixture and a set of highly interpretable gene embeddings, topic embeddings, and batch-effect linear intercepts from multiple scRNA-seq datasets. scETM is scalable to over 106 cells and confers remarkable cross-tissue and cross-species zero-shot transfer-learning performance. Using gene set enrichment analysis, we find that scETM-learned topics are enriched in biologically meaningful and disease-related pathways. Lastly, scETM enables the incorporation of known gene sets into the gene embeddings, thereby directly learning the associations between pathways and topics via the topic embeddings.

The advent of single-cell RNA sequencing (scRNA-seq) technologies has revolutionized transcriptomic studies. However, integrative analysis of scRNA-seq data remains a challenge largely due to batch effects. We present single-cell Embedded Topic Model (scETM), an unsupervised deep generative model that recapitulates known cell types by inferring the latent cell topic mixtures via a variational autoencoder. scETM is scalable to over 106 cells and enables effective knowledge transfer across datasets. scETM also offers high inter-pretability and allows the incorporation of prior pathway knowledge into the gene embeddings. The scETM-inferred topics show enrichment in cell-type-specific and disease-related pathways.

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Purpose To explore the effects of PAK4/LIMK1/Cofilin‐1 signaling pathway on the proliferation, invasion, and migration of human osteosarcoma cells. Methods The expression of PAK4/LIMK1/Cofilin‐1 was detected by immunohistochemistry in osteosarcoma tissues. The osteosarcoma cell line MG63 was transfected and divided into Mock, Control siRNA, si‐PAK4, LIMK1, and si‐PAK4+LIMK1 groups. Then, the cellular biological features of MG63 cells were detected by CCK‐8, wound‐healing, Transwell, and flow cytometry methods. The relationship of PAK4 and LIMK1 was performed by co‐immunoprecipitation test, and the protein expression of PAK4/LIMK1/Cofilin‐1 was determined by Western blotting. Finally, the effect of PAK4 on the growth of osteosarcoma was verified by subcutaneous transplantation model of osteosarcoma in nude mice. Results The expression of PAK4/LIMK1/Cofilin‐1 in both osteosarcoma tissues and cells was up‐regulated. Positive PAK4, LIMK1, and Cofilin‐1 expressions in osteosarcoma were associated with the clinical stage, distant metastasis, and tumor grade. The MG63 cell viability, migration, and invasion, as well as the expression of PAK4, p‐LIMK/LIMK, and p‐Cofilin‐1/Cofilin‐1, were restrained by the knock down of PAK4 while it promoted apoptosis. PAK4 silencing also suppressed the growth of subcutaneous transplanted tumor in nude mice. Co‐immunocoprecipitation showed that LIMK and PAK4 protein can form complex in osteosarcoma cells. Besides, LIMK1 overexpression reversed the inhibition effect of PAK4 siRNA on the growth of osteosarcoma cells. Conclusion The expression of PAK4/LIMK1/Cofilin‐1 pathway in osteosarcoma tissues was up‐regulated. Thus, PAK4 inhibition may restrict the osteosarcoma cell proliferation, invasion, and migration but promote its apoptosis via decreasing the activity of LIMK1/Cofilin‐1 pathway.